Sea-rail intermodal transportation is an essential infrastructure in global supply chains nowadays. Since the yard is the interface between sea and land, optimizing the transportation process in yards is of significant interest for increasing transportation efficiency. However, the yard management problem usually suffers from the large state space and cannot be solved effectively. We consider this important problem from a decomposition perspective, focusing on real-time scheduling in railway container yards, and make the following contributions. We show the partial decomposition property of the yard management problem. This property establishes the equivalence between joint optimization of yard components and independent optimization of each component under mild assumptions, achieving optimality and effectiveness simultaneously. Utilizing this property, we further simplify each subproblem while preserving the optima, and develop algorithms for each simplified subproblem. Numerical experiments demonstrate the performance of proposed algorithms and the contribution of optimizing each subproblem from various perspectives.

Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.

Magnetic manipulation provides a versatile, remote, noninvasive, and cost-effective strategy in a variety of applications. Till now, many different configurations of magnetic manipulation systems have been developed to address different needs on force, torque, accuracy, and accessibilities. Magnetic field mapping can help to explore the exact map of the magnetic field in the working space and guarantee the homogeneity of the magnetic field. In this paper, a flexible mapping method is employed to solve the scalar potential of the magnetic source by using the separation of variables in Cartesian coordinates. Levenberg-Marquardt Algorithm (LMA) and Whale Optimization Algorithm (WOA) are set to the solver of the model. The work is evaluated in the mapping of an eight-pole magnetic manipulation system. The result of numerical simulation shows that the coefficient of determination R2of the model reaches99.81%, and the actual system mapping obtains R2value of 99.57%. This technique can directly be used to calculate the magnetic flux density and gradient field in a short period (≈1ms). Finally, the manipulation of a permanent magnet under the control magnetic field mapping and PID controller demonstrates the effectiveness of the proposed method.

SUMMARY: Partial order alignment, which aligns a sequence to a directed acyclic graph, is now frequently used as a key component in long-read error correction and assembly. We present abPOA (adaptive banded Partial Order Alignment), a Single Instruction Multiple Data (SIMD)-based C library for fast partial order alignment using adaptive banded dynamic programming. It can work as a stand-alone multiple sequence alignment and consensus calling tool or be easily integrated into any long-read error correction and assembly workflow. Compared to a state-of-the-art tool (SPOA), abPOA is up to 10 times faster with a comparable alignment accuracy. AVAILABILITY AND IMPLEMENTATION: abPOA is implemented in C. A stand-alone tool and a C/Python software interface are freely available at https://github.com/yangao07/abPOA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatics, 2021, 37(15), 2209–2211. doi: https://doi.org/10.1093/bioinformatics/btaa963 Upon the original publication of this article, the affiliation: “Center for Bioinformatics, Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China” was inadvertently omitted prior to publication. The affiliation has been reinstated.

MOTIVATION: Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) sequencing technologies can produce long-reads up to tens of kilobases, but with high error rates. In order to reduce sequencing error, Rolling Circle Amplification (RCA) has been used to improve library preparation by amplifying circularized template molecules. Linear products of the RCA contain multiple tandem copies of the template molecule. By integrating additional in silico processing steps, these tandem sequences can be collapsed into a consensus sequence with a higher accuracy than the original raw reads. Existing pipelines using alignment-based methods to discover the tandem repeat patterns from the long-reads are either inefficient or lack sensitivity. RESULTS: We present a novel tandem repeat detection and consensus calling tool, TideHunter, to efficiently discover tandem repeat patterns and generate high-quality consensus sequences from amplified tandemly repeated long-read sequencing data. TideHunter works with noisy long-reads (PacBio and ONT) at error rates of up to 20% and does not have any limitation of the maximal repeat pattern size. We benchmarked TideHunter using simulated and real datasets with varying error rates and repeat pattern sizes. TideHunter is tens of times faster than state-of-the-art methods and has a higher sensitivity and accuracy. AVAILABILITY AND IMPLEMENTATION: TideHunter is written in C, it is open source and is available at https://github.com/yangao07/TideHunter.

MOTIVATION: RNA sequences of a gene can have single nucleotide variants (SNVs) due to single nucleotide polymorphisms (SNPs) in the genome, or RNA editing events within the RNA. By comparing RNA-seq data of a given cell type before and after a specific perturbation, we can detect and quantify SNVs in the RNA and discover SNVs with altered frequencies between distinct cellular states. Such differential variants in RNA (DVRs) may reflect allele-specific changes in gene expression or RNA processing, as well as changes in RNA editing in response to cellular perturbations or stimuli. RESULTS: We have developed rMATS-DVR, a convenient and user-friendly software program to streamline the discovery of DVRs between two RNA-seq sample groups with replicates. rMATS-DVR combines a stringent GATK-based pipeline for calling SNVs including SNPs and RNA editing events in RNA-seq reads, with our rigorous rMATS statistical model for identifying differential isoform ratios using RNA-seq sequence count data with replicates. We applied rMATS-DVR to RNA-seq data of the human chronic myeloid leukemia cell line K562 in response to shRNA knockdown of the RNA editing enzyme ADAR1. rMATS-DVR discovered 1372 significant DVRs between knockdown and control. These DVRs encompassed known SNPs and RNA editing sites as well as novel SNVs, with the majority of DVRs corresponding to known RNA editing sites repressed after ADAR1 knockdown. AVAILABILITY AND IMPLEMENTATION: rMATS-DVR is at https://github.com/Xinglab/rMATS-DVR . CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Segmentation for lesion region in ultrasound images is crucial for computer-aided diagnosis system. But it has always been a difficult task due to the defects inherent in the ultrasound images. In this paper, we propose an automatic energy-based region growing (AERG) method to automatically segment the lesion region in ultrasound images of liver. At first, the seed point of lesion region is automatically selected by sparse reconstruction algorithm. Then the region growing process is controlled by a novel energy function including both internal and external energy, so as to make the edge of the region converge to the contour of the lesion accurately and keep a small internal difference at the same time. Experiment results show that our method could improve the segmentation accuracy in comparison with other four often used segmentation methods.

The design of a wireless sensor network is introduced for the metallurgical gas monitoring, in which the sensor node support a slot-based configurable gas sensor array both for metallurgical-specific and general purposes at the factory or far regions. The key technologies to compress the multisensor vector data is discussed with an amendatory LBG vector quantization and Huffman coding algorithms. Both the proposed network design and data compression schemes are verified with the hardware prototype and practical data. To the best of our knowledge, it is a novel exploration and practice for the applications of wireless sensor networks in the metallurgical industries, especially for the metallurgical gas monitoring.

OpenFlow is a new protocol which enables researchers to run experimental protocols in a network without changing the network topology. In the paper, we analyze and test OpenFlow based on a formal method, such as CPN (colored Petri net). To avoid state exploration, we mainly focus on testing the interaction property of OpenFlow. According to the latest OpenFlow specification, we construct its hierarchy CPN model and analyze the model with CPN tools. We propose two methods to generate the test sequences covering the interaction property. We also design an algorithm to generate the test sequences automatically. The related experiments are carefully designed and executed in four kinds of network environment, respectively.

Interaction property is a natural feature of many distributed systems which finish their work on network. But most of them face state explosion when the test work is analyzed and developed with a formal model such as Petri net. In order to avoid such problems, test based on interaction property is considered. It can focus on the interesting features of a system and ignore the other irrelevant part. In this paper, some definitions related to interaction property are given. Petri net is employed to model the IUT to make use of its reachability graph. Furthermore a test sequence generation algorithm is proposed and analyzed in detail. The coverage of a test sequence is discussed according to the interaction property and the corresponding verdict methods are given. During the process of test generation, the feasibility of test execution is simultaneously considered. In order to speed up the test execution, the generated test sequences are classified by the test scenarios. The approach is illustrated on several examples.

MOTIVATION: The Affymetrix Human Exon Junction Array is a newly designed high-density exon-sensitive microarray for global analysis of alternative splicing. Contrary to the Affymetrix exon 1.0 array, which only contains four probes per exon and no probes for exon-exon junctions, this new junction array averages eight probes per probeset targeting all exons and exon-exon junctions observed in the human mRNA/EST transcripts, representing a significant increase in the probe density for alternative splicing events. Here, we present MADS+, a computational pipeline to detect differential splicing events from the Affymetrix exon junction array data. For each alternative splicing event, MADS+ evaluates the signals of probes targeting competing transcript isoforms to identify exons or splice sites with different levels of transcript inclusion between two sample groups. MADS+ is used routinely in our analysis of Affymetrix exon junction arrays and has a high accuracy in detecting differential splicing events. For example, in a study of the novel epithelial-specific splicing regulator ESRP1, MADS+ detects hundreds of exons whose inclusion levels are dependent on ESRP1, with a RT-PCR validation rate of 88.5% (153 validated out of 173 tested). AVAILABILITY: MADS+ scripts, documentations and annotation files are available at http://www.medicine.uiowa.edu/Labs/Xing/MADSplus/.

High-throughput methods such as EST sequencing, microarrays and deep sequencing have identified large numbers of alternative splicing (AS) events, but studies have shown that only a subset of these may be functional. Here we report a sensitive bioinformatics approach that identifies exons with evidence of a strong RNA selection pressure ratio (RSPR)--i.e., evolutionary selection against mutations that change only the mRNA sequence while leaving the protein sequence unchanged--measured across an entire evolutionary family, which greatly amplifies its predictive power. Using the UCSC 28 vertebrate genome alignment, this approach correctly predicted half to three-quarters of AS exons that are known binding targets of the NOVA splicing regulatory factor, and predicted 345 strongly selected alternative splicing events in human, and 262 in mouse. These predictions were strongly validated by several experimental criteria of functional AS such as independent detection of the same AS event in other species, reading frame-preservation, and experimental evidence of tissue-specific regulation: 75% (15/20) of a sample of high-RSPR exons displayed tissue specific regulation in a panel of ten tissues, vs. only 20% (4/20) among a sample of low-RSPR exons. These data suggest that RSPR can identify exons with functionally important splicing regulation, and provides biologists with a dataset of over 600 such exons. We present several case studies, including both well-studied examples (GRIN1) and novel examples (EXOC7). These data also show that RSPR strongly outperforms other approaches such as standard sequence conservation (which fails to distinguish amino acid selection pressure from RNA selection pressure), or pairwise genome comparison (which lacks adequate statistical power for predicting individual exons).

MOTIVATION: Microarray designs have become increasingly probe-rich, enabling targeting of specific features, such as individual exons or single nucleotide polymorphisms. These arrays have the potential to achieve quantitative high-throughput estimates of transcript abundances, but currently these estimates are affected by biases due to cross-hybridization, in which probes hybridize to off-target transcripts. RESULTS: To study cross-hybridization, we map Affymetrix exon array probes to a set of annotated mRNA transcripts, allowing a small number of mismatches or insertion/deletions between the two sequences. Based on a systematic study of the degree to which probes with a given match type to a transcript are affected by cross-hybridization, we developed a strategy to correct for cross-hybridization biases of gene-level expression estimates. Comparison with Solexa ultra high-throughput sequencing data demonstrates that correction for cross-hybridization leads to a significant improvement of gene expression estimates. AVAILABILITY: We provide mappings between human and mouse exon array probes and off-target transcripts and provide software extending the GeneBASE program for generating gene-level expression estimates including the cross-hybridization correction http://biogibbs.stanford.edu/~kkapur/GeneBase/.

The trans-genomic query (TGQ) problem--enabling the free query of biological information, even across genomes--is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables ? tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships, and can represent any useful connection between sequence locations. They can be curated, and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations.Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location datatype that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for Trans-Genomic Query. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

SUMMARY: Recently, the Ka/Ks ratio test, which assesses the protein-coding potentials of genomic regions based on their non-synonymous to synonymous divergence rates, has been proposed and successfully used in genome annotations of eukaryotes. We systematically performed the Ka/Ks ratio test on 925 transcript-confirmed alternatively spliced exons in the human genome, which we describe in this manuscript. We found that 22.3% of evolutionarily conserved alternatively spliced exons cannot pass the Ka/Ks ratio test, compared with 9.8% for constitutive exons. The false negative rate was the highest (85.7%) for exons with low frequencies of transcript inclusion. Analyses of alternatively spliced exons supported by full-length mRNA sequences yielded similar results, and nearly half of exons involved in ancestral alternative splicing events could not pass this test. Our analysis suggests a future direction to incorporate comparative genomics-based alternative splicing predictions with the Ka/Ks ratio test in higher eukaryotes with extensive RNA alternative splicing.