SUMMARY: Microbiome HiFi Amplicon Sequence Simulator (MHASS) creates realistic synthetic PacBio HiFi amplicon sequencing datasets for microbiome studies, by integrating genome-aware abundance modeling, realistic dual-barcoding strategies, and empirically derived pass-number distributions from actual sequencing runs. MHASS generates datasets tailored for rigorous benchmarking and validation of long-read microbiome analysis workflows, including ASV clustering and taxonomic assignment. AVAILABILITY AND IMPLEMENTATION: Implemented in Python with automated dependency management, the source code for MHASS is freely available at https://github.com/rhowardstone/MHASS along with installation instructions. Our code is also published on Zenodo at https://doi.org/10.5281/zenodo.17486364. The data underlying this article are available on GitHub at https://github.com/rhowardstone/MHASS_evaluation/.

The inference of disease transmission networks is an important problem in epidemiology. One popular approach for building transmission networks is to reconstruct a phylogenetic tree using sequences from disease strains sampled from infected hosts and infer transmissions based on this tree. However, most existing phylogenetic approaches for transmission network inference are highly computationally intensive and cannot take within-host strain diversity into account. Here, we introduce a new phylogenetic approach for inferring transmission networks, TNet, that addresses these limitations. TNet uses multiple strain sequences from each sampled host to infer transmissions and is simpler and more accurate than existing approaches. Furthermore, TNet is highly scalable and able to distinguish between ambiguous and unambiguous transmission inferences. We evaluated TNet on a large collection of 560 simulated transmission networks of various sizes and diverse host, sequence, and transmission characteristics, as well as on 10 real transmission datasets with known transmission histories. Our results show that TNet outperforms two other recently developed methods, phyloscanner and SharpTNI, that also consider within-host strain diversity. We also applied TNet to a large collection of SARS-CoV-2 genomes sampled from infected individuals in many countries around the world, demonstrating how our inference framework can be adapted to accurately infer geographical transmission networks. TNet is freely available from https://compbio.engr.uconn.edu/software/TNet/.

BACKGROUND: Personalized cancer vaccines are emerging as one of the most promising approaches to immunotherapy of advanced cancers. However, only a small proportion of the neoepitopes generated by somatic DNA mutations in cancer cells lead to tumor rejection. Since it is impractical to experimentally assess all candidate neoepitopes prior to vaccination, developing accurate methods for predicting tumor-rejection mediating neoepitopes (TRMNs) is critical for enabling routine clinical use of cancer vaccines. RESULTS: In this paper we introduce Positive-unlabeled Learning using AuTOml (PLATO), a general semi-supervised approach to improving accuracy of model-based classifiers. PLATO generates a set of high confidence positive calls by applying a stringent filter to model-based predictions, then rescores remaining candidates by using positive-unlabeled learning. To achieve robust performance on clinical samples with large patient-to-patient variation, PLATO further integrates AutoML hyper-parameter tuning, classification threshold selection based on spies, and support for bootstrapping. CONCLUSIONS: Experimental results on real datasets demonstrate that PLATO has improved performance compared to model-based approaches for two key steps in TRMN prediction, namely somatic variant calling from exome sequencing data and peptide identification from MS/MS data.

The papers in this special section were presented at the 12th International Symposium on Bioinformatics Research and Application (ISBRA), which was held at Belarusian State University in Minsk, Belarus on June 5-8, 2016.

SUMMARY: This note presents IsoEM2 and IsoDE2, new versions with enhanced features and faster runtime of the IsoEM and IsoDE packages for expression level estimation and differential expression. IsoEM2 estimates fragments per kilobase million (FPKM) and transcript per million (TPM) levels for genes and isoforms with confidence intervals through bootstrapping, while IsoDE2 performs differential expression analysis using the bootstrap samples generated by IsoEM2. Both tools are available with a command line interface as well as a graphical user interface (GUI) through wrappers for the Galaxy platform. AVAILABILITY AND IMPLEMENTATION: The source code of this software suite is available at https://github.com/mandricigor/isoem2. The Galaxy wrappers are available at https://toolshed.g2.bx.psu.edu/view/saharlcc/isoem2_isode2/. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

BACKGROUND: For fighting cancer, earlier detection is crucial. Circulating auto-antibodies produced by the patient's own immune system after exposure to cancer proteins are promising bio-markers for the early detection of cancer. Since an antibody recognizes not the whole antigen but 4-7 critical amino acids within the antigenic determinant (epitope), the whole proteome can be represented by a random peptide phage display library. This opens the possibility to develop an early cancer detection test based on a set of peptide sequences identified by comparing cancer patients' and healthy donors' global peptide profiles of antibody specificities. RESULTS: Due to the enormously large number of peptide sequences contained in global peptide profiles generated by next generation sequencing, the large number of cancer and control sera is required to identify cancer-specific peptides with high degree of statistical significance. To decrease the number of peptides in profiles generated by nextgen sequencing without losing cancer-specific sequences we used for generation of profiles the phage library enriched by panning on the pool of cancer sera. To further decrease the complexity of profiles we used computational methods for transforming a list of peptides constituting the mimotope profiles to the list motifs formed by similar peptide sequences. CONCLUSION: We have shown that the amino-acid order is meaningful in mimotope motifs since they contain significantly more peptides than motifs among peptides where amino-acids are randomly permuted. Also the single sample motifs significantly differ from motifs in peptides drawn from multiple samples. Finally, multiple cancer-specific motifs have been identified.

MOTIVATION: Next-generation sequencing (NGS) allows for analyzing a large number of viral sequences from infected patients, providing an opportunity to implement large-scale molecular surveillance of viral diseases. However, despite improvements in technology, traditional protocols for NGS of large numbers of samples are still highly cost and labor intensive. One of the possible cost-effective alternatives is combinatorial pooling. Although a number of pooling strategies for consensus sequencing of DNA samples and detection of SNPs have been proposed, these strategies cannot be applied to sequencing of highly heterogeneous viral populations. RESULTS: We developed a cost-effective and reliable protocol for sequencing of viral samples, that combines NGS using barcoding and combinatorial pooling and a computational framework including algorithms for optimal virus-specific pools design and deconvolution of individual samples from sequenced pools. Evaluation of the framework on experimental and simulated data for hepatitis C virus showed that it substantially reduces the sequencing costs and allows deconvolution of viral populations with a high accuracy. AVAILABILITY AND IMPLEMENTATION: The source code and experimental data sets are available at http://alan.cs.gsu.edu/NGS/?q=content/pooling.

There is an ever-expanding range of technologies that generate very large numbers of biomarkers for research and clinical applications. Choosing the most informative biomarkers from a high-dimensional data set, combined with identifying the most reliable and accurate classification algorithms to use with that biomarker set, can be a daunting task. Existing surveys of feature selection and classification algorithms typically focus on a single data type, such as gene expression microarrays, and rarely explore the model's performance across multiple biological data types. This paper presents the results of a large scale empirical study whereby a large number of popular feature selection and classification algorithms are used to identify the tissue of origin for the NCI-60 cancer cell lines. A computational pipeline was implemented to maximize predictive accuracy of all models at all parameters on five different data types available for the NCI-60 cell lines. A validation experiment was conducted using external data in order to demonstrate robustness. As expected, the data type and number of biomarkers have a significant effect on the performance of the predictive models. Although no model or data type uniformly outperforms the others across the entire range of tested numbers of markers, several clear trends are visible. At low numbers of biomarkers gene and protein expression data types are able to differentiate between cancer cell lines significantly better than the other three data types, namely SNP, array comparative genome hybridization (aCGH), and microRNA data. Interestingly, as the number of selected biomarkers increases best performing classifiers based on SNP data match or slightly outperform those based on gene and protein expression, while those based on aCGH and microRNA data continue to perform the worst. It is observed that one class of feature selection and classifier are consistently top performers across data types and number of markers, suggesting that well performing feature-selection/classifier pairings are likely to be robust in biological classification problems regardless of the data type used in the analysis.

BACKGROUND: Interest in de novo genome assembly has been renewed in the past decade due to rapid advances in high-throughput sequencing (HTS) technologies which generate relatively short reads resulting in highly fragmented assemblies consisting of contigs. Additional long-range linkage information is typically used to orient, order, and link contigs into larger structures referred to as scaffolds. Due to library preparation artifacts and erroneous mapping of reads originating from repeats, scaffolding remains a challenging problem. In this paper, we provide a scalable scaffolding algorithm (SILP2) employing a maximum likelihood model capturing read mapping uncertainty and/or non-uniformity of contig coverage which is solved using integer linear programming. A Non-Serial Dynamic Programming (NSDP) paradigm is applied to render our algorithm useful in the processing of larger mammalian genomes. To compare scaffolding tools, we employ novel quantitative metrics in addition to the extant metrics in the field. We have also expanded the set of experiments to include scaffolding of low-complexity metagenomic samples. RESULTS: SILP2 achieves better scalability throughg a more efficient NSDP algorithm than previous release of SILP. The results show that SILP2 compares favorably to previous methods OPERA and MIP in both scalability and accuracy for scaffolding single genomes of up to human size, and significantly outperforms them on scaffolding low-complexity metagenomic samples. CONCLUSIONS: Equipped with NSDP, SILP2 is able to scaffold large mammalian genomes, resulting in the longest and most accurate scaffolds. The ILP formulation for the maximum likelihood model is shown to be flexible enough to handle metagenomic samples.

BACKGROUND: Highly mutable RNA viruses exist in infected hosts as heterogeneous populations of genetically close variants known as quasispecies. Next-generation sequencing (NGS) allows for analysing a large number of viral sequences from infected patients, presenting a novel opportunity for studying the structure of a viral population and understanding virus evolution, drug resistance and immune escape. Accurate reconstruction of genetic composition of intra-host viral populations involves assembling the NGS short reads into whole-genome sequences and estimating frequencies of individual viral variants. Although a few approaches were developed for this task, accurate reconstruction of quasispecies populations remains greatly unresolved. RESULTS: Two new methods, AmpMCF and ShotMCF, for reconstruction of the whole-genome intra-host viral variants and estimation of their frequencies were developed, based on Multicommodity Flows (MCFs). AmpMCF was designed for NGS reads obtained from individual PCR amplicons and ShotMCF for NGS shotgun reads. While AmpMCF, based on covering formulation, identifies a minimal set of quasispecies explaining all observed reads, ShotMCS, based on packing formulation, engages the maximal number of reads to generate the most probable set of quasispecies. Both methods were evaluated on simulated data in comparison to Maximum Bandwidth and ViSpA, previously developed state-of-the-art algorithms for estimating quasispecies spectra from the NGS amplicon and shotgun reads, respectively. Both algorithms were accurate in estimation of quasispecies frequencies, especially from large datasets. CONCLUSIONS: The problem of viral population reconstruction from amplicon or shotgun NGS reads was solved using the MCF formulation. The two methods, ShotMCF and AmpMCF, developed here afford accurate reconstruction of the structure of intra-host viral population from NGS reads. The implementations of the algorithms are available at http://alan.cs.gsu.edu/vira.html (AmpMCF) and http://alan.cs.gsu.edu/NGS/?q=content/shotmcf (ShotMCF).

This special section includes a selection of papers presented at the Eighth International Symposium on Bioinformatics Research and Application (ISBRA), which was held in Dallas, Texas, on 21-23 May 2012. The ISBRA symposium provides a forum for the exchange of ideas and results among researchers, developers, and practitioners working on all aspects of bioinformatics and computational biology and their applications. In 2012, 66 papers were submitted in response to the call for papers, out of which 26 papers appeared in the ISBRA proceedings published as volume 7292 of Springer Verlag's Lecture Notes in Bioinformatics series. Extended versions of nine symposium papers were invited and accepted for publication in this special section following a rigorous review process. The selected papers cover a broad range of bioinformatics topics, including biological networks, computational complexity of problems in structural biology and genomics, and phylogenetic inference and analysis. Herein, we briefly introduce each of them.

This Supplement includes a selection of papers presented at the 7th International Symposium on Bioinformatics Research and Application (ISBRA), which was held on May 27-29, 2011 at Central South University in Changsha, China.The technical program of the symposium included 36 extended abstracts presented orally and published in volume 6674 of Springer Verlag's Lecture Notes in Bioinformatics series.Additionally, the program included 38 short abstracts presented either orally or as posters.Authors of both extended and short abstracts presented at the symposium were invited to submit full versions of their work to this Supplement.Following a rigorous review process, 19 of the 40 full papers submitted were selected for publication.Selected papers cover a broad range of bioinformatics topics, ranging from algorithms for structural biology to phylogenetics and biological networks.The first two papers of the Supplement address two important problems in structural biology.Improved methods for predicting protein-protein and protein-DNA binding and identification of binding sites are critical components of rational drug design and functional annotation pipelines.The paper by Guo and Wang proposes an efficient algorithm for finding similar binding sites on the protein surfaces based on sequence alignment, protein surface detection, and 3D structure comparison.Validation experiments show significantly improved average recall and precision values compared with existing approaches.Szabóová et al. propose methods for predicting protein-DNA binding propensity from spatial structure information without the use of evolutionary information.Such methods are particularly useful for optimizing DNA-binding of engineered proteins, for which evolutionary information is not available.Unlike previous approaches that rely on ad-hoc sets of physicochemical

Recent advances in DNA sequencing have made it possible to sequence the whole transcriptome by massively parallel sequencing, commonly referred as RNA-Seq. RNA-Seq is quickly becoming the technology of choice for transcriptome research and analyses. RNA-Seq allows to reduce the sequencing cost and significantly increase data throughput, but it is computationally challenging to use such RNA-Seq data for reconstructing of full length transcripts and accurately estimate their abundances across all cell types. A number of recent works have addressed the problem of transcriptome reconstruction from RNA-Seq reads. These methods fall into three categories: genome-guided, genome-independent and annotation-guided. In this work, we propose a novel statistical genome-guided method called “ T ranscriptome R econstruction using I nteger P rograming” (TRIP) that incorporates fragment length distribution into novel transcript reconstruction from paired-end RNA-Seq reads. To reconstruct novel transcripts, we create a splice graph based on inferred exon boundaries and RNA-Seq reads. A splice graph is a directed acyclic graph (DAG), whose vertices represent exons and edges represent splicing events. We enumerate all maximal paths in the splice graph using a depth-first-search (DFS) algorithm. These paths correspond to putative transcripts and are the input for the TRIP algorithm. To solve the transcriptome reconstruction problem we must select a set of putative transcripts with the highest support from the RNA-Seq reads. We formulate this problem as an integer program. The objective to select the smallest set of putative transcripts that yields a good statistical fit between the fragment length distribution empirically determined during library preparation and fragment lengths implied by mapping read pairs to selected transcripts. Preliminary experimental results on synthetic datasets generated with various sequencing parameters and distribution assumptions show that TRIP has increased transcriptome reconstruction accuracy compared to previous methods that ignore fragment length distribution information.

BACKGROUND: RNA viruses infecting a host usually exist as a set of closely related sequences, referred to as quasispecies. The genomic diversity of viral quasispecies is a subject of great interest, particularly for chronic infections, since it can lead to resistance to existing therapies. High-throughput sequencing is a promising approach to characterizing viral diversity, but unfortunately standard assembly software was originally designed for single genome assembly and cannot be used to simultaneously assemble and estimate the abundance of multiple closely related quasispecies sequences. RESULTS: In this paper, we introduce a new Viral Spectrum Assembler (ViSpA) method for quasispecies spectrum reconstruction and compare it with the state-of-the-art ShoRAH tool on both simulated and real 454 pyrosequencing shotgun reads from HCV and HIV quasispecies. Experimental results show that ViSpA outperforms ShoRAH on simulated error-free reads, correctly assembling 10 out of 10 quasispecies and 29 sequences out of 40 quasispecies. While ShoRAH has a significant advantage over ViSpA on reads simulated with sequencing errors due to its advanced error correction algorithm, ViSpA is better at assembling the simulated reads after they have been corrected by ShoRAH. ViSpA also outperforms ShoRAH on real 454 reads. Indeed, 7 most frequent sequences reconstructed by ViSpA from a real HCV dataset are viable (do not contain internal stop codons), and the most frequent sequence was within 1% of the actual open reading frame obtained by cloning and Sanger sequencing. In contrast, only one of the sequences reconstructed by ShoRAH is viable. On a real HIV dataset, ShoRAH correctly inferred only 2 quasispecies sequences with at most 4 mismatches whereas ViSpA correctly reconstructed 5 quasispecies with at most 2 mismatches, and 2 out of 5 sequences were inferred without any mismatches. ViSpA source code is available at http://alla.cs.gsu.edu/~software/VISPA/vispa.html. CONCLUSIONS: ViSpA enables accurate viral quasispecies spectrum reconstruction from 454 pyrosequencing reads. We are currently exploring extensions applicable to the analysis of high-throughput sequencing data from bacterial metagenomic samples and ecological samples of eukaryote populations.

BACKGROUND: Recent technology advances have enabled sequencing of individual genomes, promising to revolutionize biomedical research. However, deep sequencing remains more expensive than microarrays for performing whole-genome SNP genotyping. RESULTS: In this paper we introduce a new multi-locus statistical model and computationally efficient genotype calling algorithms that integrate shotgun sequencing data with linkage disequilibrium (LD) information extracted from reference population panels such as Hapmap or the 1000 genomes project. Experiments on publicly available 454, Illumina, and ABI SOLiD sequencing datasets suggest that integration of LD information results in genotype calling accuracy comparable to that of microarray platforms from sequencing data of low-coverage. A software package implementing our algorithm, released under the GNU General Public License, is available at http://dna.engr.uconn.edu/software/GeneSeq/. CONCLUSIONS: Integration of LD information leads to significant improvements in genotype calling accuracy compared to prior LD-oblivious methods, rendering low-coverage sequencing as a viable alternative to microarrays for conducting large-scale genome-wide association studies.

Digital microfluidic biochips (DMFBs) are rectangular arrays of electrodes, or cells, that enable precise manipulation of nanoliter-sized droplets of biological fluids and chemical reagents. Because of the safety-critical nature of their applications, biochips must be tested frequently, both off-line (e.g., postmanufacturing) and concurrent with assay execution. Under both scenarios, testing is accomplished by routing one or more test droplets across the chip and recording their arrival at the destination. In this paper, we formalize the DMFB-testing problem under the common objective of completion time minimization, including previously ignored constraints of droplet noninterference. Our contributions include a proof that the general version of the problem is NP-hard, tight lower bounds for both off-line and concurrent testing, optimal and approximation algorithms for off-line testing of commonly used rectangular shaped biochips, as well as a concurrent testing heuristic producing solutions within 23%–34% of the lower bound in experiments conducted on data sets simulating varying percentages of biochip cells occupied by concurrently running assays.

The six papers in this special section cover a broad range of bioinformatics topics, ranging from comparative genomics and phylogenetics to population genetics, and from RNA structure prediction to analysis of protein-protein interaction networks.

The five papers in this special section were presented at the Fourth International Symposium on Bioinformatics Research and Application (ISBRA), held at Georgia State University in Atlanta, GA, on 6-9 May 2008.

To achieve increased throughput, amplification of multiple DNA sequences is often performed using a single Polymerase Chain Reaction (PCR) called Multiplex PCR (MP-PCR). Successful MP-PCR requires efficient methods for selecting sets of synthetic oligonucleotides called primers that collectively amplify all DNA loci of interest. Since the potential for forming primer-dimer pairs and unintended amplification products increases with the number of primers, a common optimization objective is to minimize the number of primers required to amplify all targets. Significant reductions in the number of required primers can be achieved by using primers with degenerate bases, or degenerate primers. The problem of selecting the minimum number of degenerate primers that amplify a given set of loci, referred to as the Multiple Degenerate Primer Selection Problem (MDPSP) has received much attention from researchers in the past few years. Since several variants of the problem have been proved to be NP-Complete, research has focused on heuristic algorithms that perform well on real biological data. In this paper, we present two new greedy algorithms for MDPSP, analyze their time and space complexities and compare their performance on random and real biological data with that of two previously reported algorithms. Our results show that the execution time and memory requirement of proposed algorithms is less than of existing algorithms, thus enabling the processing of larger input sets. Also, the new algorithms eliminate the dependency of the previous algorithms on an empirical input parameter that affects the runtime and quality of output. The software is downloadable at http://www.engr.uconn.edu/˜sub02005/software.html

A Single Nucleotide Polymorphism (SNP) is a position in the genome at which two or more of the possible four nucleotides occur in a large percentage of the population. SNPs account for most of the genetic variability between individuals,and mapping SNPs in the human population has become the next high-priority in genomics after the completion of the Human Genome project. In diploid organisms such as humans, there are two non-identical copies of each autosomal chromosome. A description of the SNPs in a chromosome is called a haplotype. At present, it is prohibitively expensive to directly determine the haplotypes of an individual, but it is possible to obtain rather easily the conflated SNP information in the so called genotype. Computational methods for genotype phasing, i.e., inferring haplotypes from genotype data, have received much attention in recent years as haplotype information leads to increased statistical power of disease association tests. However, many of the existing algorithms have impractical running time for phasing large genotype data sets such as those generated by the international HapMap project. In this paper we propose a highly scalable algorithm based on entropy minimization. Our algorithm is capable of phasing both unrelated and related genotypes coming from complex pedigrees. Experimental results on both real and simulated datasets show that our algorithm achieves a phasing accuracy worse but close to that of best existing methods while being several orders of magnitude faster. The open source code implementation of the algorithm and a web interface are publicly available at http://dna.engr.uconn.edu/~software/ent/.

The special section includes a selection of papers presented at the Third International Symposium on Bioinformatics Research and Application (ISBRA 2007). which took place at Georgia State University, Atlanta, 7-10 May 2007.

The aggressive scaling of very large-scale integration feature size and the pervasive use of advanced reticle enhancement technologies lead to dramatic increases in mask costs, pushing prototype and low-volume production designs to the limit of economic feasibility. Multiproject wafers (MPWs), or “shuttle” runs, provide an attractive solution for such designs by providing a mechanism to share the cost of mask tooling among up to tens of designs. However, MPW reticle floorplanning and wafer dicing introduce complexities that are not encountered in typical single-project wafers. Recent works on wafer dicing adopt one or more of the following assumptions to reduce problem complexity: 1) equal production volume requirement for all designs; 2) same dicing plan used for all wafers or for all rows/columns of reticle images on a wafer; 3) unrealistic wafer models such as a rectangular array of projections; and 4) fixed wafer shot-map. Although using one or more of the aforementioned assumptions makes the problem solvable, the performance of the solutions is degraded. In this paper, a comprehensive MPW flow aimed at minimizing the number of wafers needed to fulfill given die production volumes is proposed. The proposed flow includes two main steps: 1) multiproject reticle floorplanning and 2) wafer shot-map and dicing plan definition. For each of these steps, improved algorithms are proposed as follows. The proposed reticle floorplanner uses a hierarchical quadrisection combined with simulated annealing to generate “diceable” floorplans, observing given maximum reticle sizes. The proposed dicing planner allows multiple side-to-side dicing plans for different wafers and different reticle projection rows/columns within a wafer and further improves the dicing yield by partitioning each wafer into a small number of parts before individual die extraction. A wafer shot-map definition heuristic is also proposed in order to fully utilize round wafer real estate by extracting the maximum number of functional dies from both fully and partially printed reticle images. Experiments on industry test cases show that the proposed methods outperform significantly not only previous methods in the literature but also reticle floorplans manually designed by experienced engineers.

DNA probe arrays, or DNA chips, have emerged as a core genomic technology that enables cost-effective gene expression monitoring, mutation detection, single nucleotide polymorphism analysis, and other genomic analyses. DNA chips are manufactured through a highly scalable process called very large-scale immobilized polymer synthesis (VLSIPS) that combines photolithographic technologies adapted from the semiconductor industry with combinatorial chemistry. Commercially available DNA chips contain more than half a million probes and are expected to exceed 100 million probes in the next generation. This paper is one of the first attempts to apply very large scale integration (VLSI) computer-aided design methods to the physical design of DNA chips, where the main objective is to minimize total border cost (i.e., the number of nucleotide mismatches between adjacent sites). By exploiting analogies between manufacturing processes for DNA arrays and for VLSI chips, the authors demonstrate the potential for transfer of methodologies from the 40-year-old field of electronic design automation to the newer DNA array design field. The main contributions of this paper are the following. First, it proposes several partitioning-based algorithms for DNA probe placement that improve solution quality by over 4% compared to best previously known methods. Second, it gives a new design flow for DNA arrays, which enhances current methodologies by adding flow awareness to each optimization step and introducing feedback loops. Third, it proposes solution methods for new formulations integrating multiple design steps, including probe selection, placement, and embedding. Finally, it introduces new techniques to experimentally evaluate the scalability and suboptimality of existing and newly proposed probe placement algorithms. Interestingly, the authors find that DNA placement algorithms appear to have better suboptimality properties than those recently reported for VLSI placement algorithms [C.C. Chang et al., Optimality and scalability study of existing placement algorithms, Proc. Asia South-Pacific Design Automation Conf., Kitakyushu, Japan, p.621-7, Jan. 2003; J. Cong et al., Optimality, scalability and stability study of partitioning and placement algorithms, Proc. Int. Symp. Physical Design (ISPD), Monterey, CA, p.88-94, 2003]

Summary: DNA-BAR is a software package for selecting DNA probes (henceforth referred to as distinguishers) that can be used in genomic-based identification of microorganisms. Given the genomic sequences of the microorganisms, DNA-BAR finds a near-minimum number of distinguishers yielding a distinct hybridization pattern for each microorganism. Selected distinguishers satisfy user specified bounds on length, melting temperature and GC content, as well as redundancy and cross-hybridization constraints. Availability: DNA-BAR can be used online through the web interface provided at http://dna.engr.uconn.edu/~software/DNA-BAR/. The open source C code, released under the GNU General Public License, is also available at the above address. Contact: [email protected]

The Y architecture for on-chip interconnect is based on pervasive use of 0/spl deg/, 120/spl deg/, and 240/spl deg/ oriented semiglobal and global wiring. Its use of three uniform directions exploits on-chip routing resources more efficiently than traditional Manhattan wiring architecture. This paper gives in-depth analysis of deployment issues associated with the Y architecture. Our contributions are as follows. 1) We analyze communication capability (throughput of meshes) for different interconnect architectures using a multicommodity flow approach and a Rentian communication model. Throughput of the Y architecture is largely improved compared to the Manhattan architecture, and is close to the throughput of the X architecture. 2) We improve existing estimates for the wirelength reduction of various interconnect architectures by taking into account the effect of routing-geometry-aware placement. 3) We propose a symmetrical Y clock tree structure with better total wire length compared to both H and X clock tree structures, and better path length compared to the H tree. 4) We discuss power distribution under the Y architecture, and give analytical and SPICE simulation results showing that the power network in Y architecture can achieve (8.5%) less IR drop than an equally resourced power network in Manhattan architecture. 5) We propose the use of via tunnels and banks of via tunnels as a technique for improving routability for Manhattan and Y architectures.

Path delay fault testing has become increasingly important due to higher clock rates and higher process variability caused by shrinking geometries. Achieving high-coverage path delay fault testing requires the application of scan justified test vector pairs, coupled with careful ordering of the scan flip-flops and/or insertion of dummy flip-flops in the scan chain. Previous works on scan synthesis for path delay fault testing using scan shifting have focused exclusively on maximizing fault coverage and/or minimizing the number of dummy flip-flops, but have disregarded the scan wirelength overhead. In this paper we propose a layout-aware coverage-driven scan chain ordering methodology and give exact and heuristic algorithms for computing the achievable tradeoffs between path delay fault coverage and both dummy flip-flop and wirelength costs. Experimental results show that our scan chain ordering methodology yields significant improvements in path delay coverage with a very small increase in wirelength overhead compared to previous layout-driven approaches, and similar coverage with up to 25 times improvement in wirelength compared to previous layout-oblivious coverage-driven approaches.

Multi-project Wafers (MPW) are an efficient way to share the rising costs of mask tooling between multiple prototype and low production volume designs. Packing the different die images on a multi-project reticle leads to new and highly challenging floorplanning formulations, characterized by unusual constraints and complex objective functions. In this paper we study multi-project reticle floorplanning and wafer dicing problems under the prevalent side-to-side wafer dicing technology. Our contributions include practical mathematical programming algorithms and efficient heuristics based on interval-graph coloring which find side-to-side wafer dicing plans with maximum yield for a fixed multi-project reticle floorplan and given per-die maximum dicing margins. We also give novel shelf packing and simulated annealing reticle floorplanning algorithms for maximizing wafer-dicing yield. Experimental results show that our algorithms improve wafer-dicing yield significantly compared to existing industry tools and academic min-area floorplanners.

We propose to introduce redundant interconnects for manufacturing yield and reliability improvement. By introducing redundant interconnects, the potential for open faults is reduced, at the cost of increased potential for short faults. Overall, manufacturing yield and fault tolerance can be improved. We focus on a postprocessing, tree-augmentation approach, which can be easily integrated in current physical design flows. Our contributions are as follows. 1) We formulate the problem as a variant of the classical two-edge-connectivity augmentation problem in which we take into account such practical issues as wirelength increase budget, routing obstacles, and the use of Steiner points. 2) We show that an optimum solution can always be found on the Hanan grid defined by the terminals and the corners of the feasible routing region. 3) We give a compact integer program formulation which is solved in practical runtime by the commercial optimization package CPLEX for nets with up to 100 terminals. 4) We give a well-scaling greedy algorithm which has a practical runtime up to 1000 terminals, and comes on the average within 1%-2% of the optimum computed by CPLEX. 5). We give a comprehensive experimental study comparing the solution quality and runtime of our methods with the best methods reported in the literature.

The rectilinear Steiner minimum tree (RSMT) problem, which asks for a minimum-length interconnection of a given set of terminals in the rectilinear plane, is one of the fundamental problems in electronic design automation. Recently there has been renewed interest in this problem due to the need for highly scalable algorithms able to handle nets with tens of thousands of terminals. In this paper we give a practical O (n log2 n) heuristic for computing near-optimal rectilinear Steiner trees based on a batched version of the greedy triple contraction algorithm of Zelikovsky [21]. Experiments conducted on both random and industry testcases show that our heuristic matches or exceeds the quality of best known RSMT heuristics, e.g., on random instances with more than 100 terminals our heuristic improves over the rectilinear minimum spanning tree by an average of 11%. Moreover, our heuristic has very well scaling runtime, e.g., it can route a 34k-terminals net extracted from a real design in less than 25 seconds compared to over 86 minutes needed by the O(n2) edge-based heuristic of Borah, Owens, and Irwin [3]. Since our heuristic is graph-based, it can be easily modified to handle practical considerations such as routing obstacles, preferred directions, via costs, and octilinear routing - indeed, experimental results show only a small factor increase in runtime when switching from rectilinear to octilinear routing.

The QoS Steiner tree problem asks for the most cost-efficient way to multicast multimedia to a heterogeneous collection of users with different consumption rates. We assume that the cost of using a link is not constant, but rather depends on the maximum bandwidth routed through the link. Formally, given a graph with costs on the edges, a source node and a set of terminal nodes, each one with a bandwidth requirement, the goal is to find a Steiner tree containing the source and the cheapest assignment of bandwidth to each of its edges so that each source-to-terminal path in the tree has bandwidth at least as large as the bandwidth required by the terminal. Our main contributions are: (1) new covering-type integer linear program formulations for the problem; (2) two new heuristics based on the primal-dual framework; (3) a primal-dual constant-factor approximation algorithm; (4) an extensive experimental study of the new heuristics and of several previously proposed algorithms.

DNA probe arrays have recently emerged as one of the core genomic technologies. Exploiting analogies between manufacturing processes for DNA arrays and for VLSI chips, we demonstrate the potential for transfer of methodologies from the 40-year old field of electronic design automation to the newer DNA array design field. Our main contributions are the following. (1) We give a new design flow for DNA arrays which enhances current methodologies by adding flow-awareness to each optimization step and introducing feedback loops. (2) We propose solution methods for new formulations integrating multiple design steps, including probe selection, placement, and embedding. (3) We give results of a comprehensive experimental study showing that significant improvements in solution quality can be achieved by using the enhanced methodologies.

Design of DNA arrays for very large-scale immobilized polymer synthesis (VLSIPS) [8] seeks to minimize effects of unintended illumination during mask exposure steps. [9, 14] formulate this requirement as the Border Minimization Problem and give methods for placement (at array sites) and embedding (in the mask sequence) of probes in both synchronous and asynchronous regimes. These previous methods do not address several practical details of the application and, more critically, are not scalable to the O(108) probes contemplated for next-generation probe arrays. In this work, we make two main contributions:

We study the problem of assigning transmission ranges to the nodes of ad hoc wireless networks to minimize power consumption while ensuring network connectivity. We give an exact branch and cut algorithm based on a new integer linear program formulation solving instances with up to 35-40 nodes in 1 hour; a proof that min-power symmetric connectivity with asymmetric power requirements is inapproximable within factor (1 - /spl epsi/) ln |V| for any /spl epsi/ > 0 unless P = NP; an improved analysis for two approximation algorithms recently proposed by Calinescu et al. (TCS'02), decreasing the best known approximation factor to 5/3 + /spl epsi/; and a comprehensive experimental study comparing new and previously proposed heuristics with the above exact and approximation algorithms.

Bounding the load capacitance at gate outputs is a standard element in today's electrical correctness methodologies for high-speed digital very large scale integration design. Bounds on load caps improve coupling-noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise (Kahng et al. 1998). For clock and test distribution, an additional design requirement is bounding the buffer skew, i.e., the difference between the maximum and the minimum number of buffers over all of the source-to-sink paths in the routing tree, since buffer skew is one of the main factors affecting delay skew (Tellez and Sarrafzadeh 1997). In this paper, we consider algorithms for buffering a given tree with the minimum number of buffers under given load cap and buffer skew constraints. We show that the greedy algorithm proposed by Tellez and Sarrafzadeh is suboptimal for nonzero buffer-skew bounds and give examples showing that no bottom-up greedy algorithm can achieve optimality. The main contribution of the paper is an optimal dynamic programming algorithm for the problem. Experiments on test cases extracted from recent industrial designs show that the dynamic programming algorithm has practical running time and saves up to 37.5% of the buffers inserted by Tellez and Sarrafzadeh's algorithm.

In high-speed digital VLSI design, bounding the load capacitance at gate outputs is a well-known methodology to improve coupling noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise. Bounding load capacitance also improves reliability with respect to hot-carrier oxide breakdown and AC self-heating in interconnects, and guarantees bounded input rise/fall times at buffers and sinks. This paper introduces a new minimum-buffer routing problem (MBRP) formulation which requires that the capacitive load of each buffer, and of the source driver, be upper-bounded by a given constant. Our contributions are as follows: We give linear-time algorithms for optimal buffering of a given routing tree with a single (inverting or noninverting) buffer type. For simultaneous routing and buffering with a single noninverting buffer type, we prove that no algorithm can guarantee a factor smaller than 2 unless P=NP and give an algorithm with approximation factor slightly larger than 2 for typical buffers. For the case of a single inverting buffer type, we give an algorithm with approximation factor slightly larger than 4. We give local-improvement and clustering based MBRP heuristics with improved practical performance, and present a comprehensive experimental study comparing the runtime/quality tradeoffs of the proposed MBRP heuristics on test cases extracted from recent industrial designs.

We propose to introduce redundant interconnects for manufacturing yield and reliability improvement. By introducing redundant interconnects, the potential for open faults is reduced at the cost of increased potential for short faults; overall, manufacturing yield and fault tolerance can be improved. We focus on a post-processing, tree augmentation approach which can be easily integrated in current physical design flows. Our contributions are as follows:• We formulate the problem as a variant of the classical 2-edge-connectivity augmentation problem in which we take into account such practical issues as wirelength increase budget, routing obstacles, and use of Steiner points.• We show that an optimum solution can always be found on the Hanan grid defined by the terminals and the corners of the feasible routing region.• We give a compact integer program formulation which, for up to 100 terminal nets, is solved in practical runtime by the commercial optimization package CPLEX.• We give a well-scaling greedy algorithm which has practical runtime up to 1,000 terminals, and comes on the average within 1--2% of the optimum computed by CPLEX.• We give a comprehensive experimental study comparing the solution quality and runtime of our methods with the best reported methods for 2-edge-connectivity augmentation, including a sophisticated heuristic based on minimum-weight branchings [9] and a recent genetic algorithm [14].Experiments on randomly generated and industry testcases show that our greedy augmentation method achieves significant increase in reliability (as measured by the percentage of biconnected tree edges) with very small increase in wirelength. For example, on 1,000 terminal nets the average percentage of biconnected tree edges is 34.19% for a wire-length increase of only 1%, and 87.73% for a wirelength increase of 20%. SPICE simulations on industry routed nets show that non-tree routing has the additional benefit of reducing maximum sink delay by an average of 28.26% compared to Steiner routing, and by an average of 3.72% compared to timing optimized routing. SPICE simulations further imply that non-tree routing has smaller delay variation due to process variability.

To implement high-performance global interconnect without impacting the placement and performance of existing blocks, the use of buffer blocks is becoming increasingly popular in structured-custom and block-based application specified integrated circuit methodologies. We address the problem of how to perform the buffering of global multiterminal nets given an existing buffer block plan. We give provably good and heuristic algorithms for this problem. The method routes connections using available buffer blocks, such that required upper and lower bounds on buffer intervals are satisfied. In addition, the algorithms allow more than one buffer to be inserted into any given connection and observe upper bounds and parity constraints on the number of buffers per connection. Most importantly, and unlike previous works on the problem, we take into account: 1) multiterminal nets; 2) multiple routing layers; 3) simultaneous buffered routing and compaction; and 4) buffer libraries. Our method outperforms existing algorithms for the problem, based on two-pin decompositions of the nets, and has been validated on top-level layouts extracted from a recent high-end microprocessor design.

To implement high-performance global interconnect without impacting the placement and performance of existing blocks, the use of buffer blocks is becoming increasingly popular in structured-custom and block-based ASIC methodologies. Recent works by Cong, Kong and Pan [5] and Tang and Wong [18] give algorithms to solve the buffer block planning problem. In this paper, we address the problem of how to perform buffering of global multiterminal nets given an existing buffer block plan. We give a provably good algorithm based on a recent approach of Garg and Könemann [8] and Fleischer [7] (see also Albrecht [1] and Dragan et al. [6]). Our method routes connections using available buffer blocks, such that required upper and lower bounds on buffer intervals - as well as wirelength upper bounds per connection - are satisfied. In addition, our algorithm allows more than one buffer to be inserted into any given connection and observes buffer parity constraints. Most importantly, and unlike previous works on the problem [5, 18, 6], we take into account multiterminal nets. Our algorithm outperforms existing algorithms for the problem [5, 6], which are based on 2-pin decompositions of the nets. The algorithm has been validated on top-level layouts extracted from a recent high-end microprocessor design.

In high-speed digital VLSI design, bounding the load capacitance at gate outputs is a well-known methodology to improve coupling noise immunity, reduce degradation of signal transition edges, and reduce delay uncertainty due to coupling noise. Bounding load capacitance also improves reliability with respect to hot-carrier oxide breakdown and AC self-heating in interconnects, and guarantees bounded input rise/fall times at buffers and sinks. This paper introduces a new minimum-buffer routing problem (MBRP) formulation which requires that the capacitive load of each buffer, and of the source driver, be upper-bounded by a given constant. Our contributions include the following. (i) We give linear-time algorithms for optimal buffering of a given routing tree with a single (inverting or noninverting) buffer type. (ii) For simultaneous routing and buffering with a single noninverting buffer type, we give a factor 2(1+/spl epsiv/) approximation algorithm and prove that no algorithm can guarantee a factor smaller than 2 unless P=NP. For the case of a single inverting buffer type, we give a factor 4(1+/spl epsiv/) approximation algorithm. (iii) We give local-improvement and clustering based MBRP heuristics with improved practical performance, and present a comprehensive experimental study comparing the runtime/quality trade-offs of the proposed MBRP heuristics on test cases extracted from recent industrial designs.

The skew of an edge-weighted rooted tree is the maximum difference between any two root-to-leaf path weights. Zero- or bounded-skew trees are needed for achieving synchronization in many applications, including network multicasting [G. N. Rouskas and I. Baldine, IEEE J. on Selected Areas in Communication, 15 (1997), pp. 346--356] and VLSI clock routing [H. Bakoglu, Circuits, Interconnections, and Packaging for VSLI, Addison-Wesley, Reading, MA, 1990, A. B. Kahng and G. Robins, On Optimal Interconnections for VSLI, Kluwer Academic Publishers, Norwell, MA, 1995]. In these applications edge weights represent propagation delays, and a signal generated at the root should be received by multiple recipients located at the leaves (almost) simultaneously. The objective is to find zero- or bounded-skew trees of minimum total weight, since the weight of the tree is directly proportional to the amount of resources (bandwidth and buffers for network multicasting, power and chip area for clock routing in VLSI) that must be allocated to the tree. Charikar et al. in [Proceedings of the Tenth ACM-SIAM Symposium on Discrete Algorithms, Baltimore, MD, 1999, ACM, New York, 1999, pp. 177--184] have recently proposed the first strongly polynomial algorithms with proven constant approximation factors, $2e\approx 5.44 and 16.86, for finding minimum weight zero- and bounded-skew trees, respectively. In this paper we introduce a new approach to these problems, based on zero-skew "stretching" of spanning trees, and obtain algorithms with improved approximation factors of 4 and 14. For the case when tree nodes are points in the plane and edge weights are given by the rectilinear metric our algorithms find zero- and bounded-skew trees of length at most 3 and 9 times the optimum. This case is of special interest in VLSI clock routing. An important feature of our algorithms is their practical running time, which is asymptotically the same as the time needed for computing the minimum spanning tree.

To implement high-performance global interconnect without impacting the performance of existing blocks, the use of buffer blocks is increasingly popular in structured-custom and block-based ASIC/SOC methodologies. Recent works by Cong et al. (1999) and Tang and Wong (2000) give algorithms to solve the buffer block planning problem. In this paper we address the problem of how to perform buffering of global nets given an existing buffer block plan. Assuming that global nets have been already decomposed into two-pin connections, we give a provably good algorithm based on a recent approach of Garg and Konemann (1998) and Fleischer (1999). Our method routes connections using available buffer blocks, such that required upper and lower bounds on buffer intervals-as well as wirelength upper bounds per connection-are satisfied. Our model allows more than one buffer to be inserted into any given connection. In addition, our algorithm observes buffer parity constraints, i.e., it will choose to use an inverter or a buffer (=co-located pair of inverters) according to source and destination signal parity. The algorithm outperforms previous approaches and has been validated on top-level layouts extracted from a recent high-end microprocessor design.

The minimum rectilinear Steiner tree (RST) problem is one of the fundamental problems in the field of electronic design automation. The problem is NP-hard, and much work has been devoted to designing good heuristics and approximation algorithms; to date, the champion in solution quality among RST heuristics is the Batched Iterated 1-Steiner (BI1S) heuristic of Kahng and Robins. In a recent development, exact RST algorithms have witnessed spectacular progress: The new release of the GeoSteiner code of Warme et al. has average running time comparable to that of the fastest available BI1S implementation, due to Robins. We are, thus, faced with the paradoxical situation that an exact algorithm for an NP-hard problem is competitive in speed with a state of-the-art heuristic for the problem. The main contribution of this paper is a new RST heuristic, which has at its core a recent 3/2 approximation algorithm of Rajagopalan and Vazirani for the metric Steiner tree problem on quasi-bipartite graphs-these are graphs that do not contain edges connecting pairs of Steiner vertices. The RV algorithm is built around the linear programming relaxation of a sophisticated integer program formulation, called the bidirected cut relaxation. Our heuristic achieves a good running time by combining an efficient implementation of the RV algorithm with simple, but powerful geometric reductions. Experiments conducted on both random and real very large scale integrated instances show that the new RST heuristic runs significantly faster than Robins' implementation of BI1S and than the GeoSteiner code. Moreover, the new heuristic typically gives higher-quality solutions than BI1S.

The minimum rectilinear Steiner tree (RST) problem is one of the fundamental problems in the field of electronic design automation. The problem is NP-hard, and much work has been devoted to designing good heuristics and approximation algorithms; to date, the champion in solution quality among RST heuristics is the Batched Iterated 1-Steiner (BI1S) heuristic of Kahng and Robins (1992). In a recent development, exact RST algorithms have witnessed spectacular progress: the new release of the GeoSteiner code of Warme, Winter, and Zachariasen (1998) has average running time comparable to that of the fastest available Bl1S implementation, due to Robins. We are thus faced with the paradoxical situation that an exact algorithm for an NP-hard problem is competitive in speed with a state-of-the-art heuristic for the problem. The main contribution of this paper is a new RST heuristic, which has at its core a recent 3/2 approximation algorithm of Rajagopalan and Vazirani (1999) for the metric Steiner tree problem on quasi-bipartite graphs-these are graphs that do not contain edges connecting pairs of Steiner vertices. The RV algorithm is built around the linear programming relaxation of a sophisticated integer program formulation, called the bidirected cut relaxation. Our heuristic achieves a good running time by combining an efficient implementation of the RV algorithm with simple, but powerful geometric reductions. Experiments conducted on both random and real VLSI instances show that the new RST heuristic runs significantly faster than Robins' implementation of BI1S and than the GeoSteiner code. Moreover, the new heuristic typically gives higher-quality solutions than Bl1S.

The problem of minimizing the trellis complexity of a code by coordinate permutation is studied. Three measures of trellis complexity are considered: the total number of states, the total number of edges, and the maximum state complexity of the trellis. The problem is proven NP-hard for all three measures, provided the field over which the code is specified is not fixed. We leave open the problem of dealing with the case of a fixed field, in particular GF(2).