Optimal intervention planning is a critical part of epidemiological control, which is difficult to attain in real life situations. Ordinary differential equation (ODE) models can be used to optimize control but the results can not be easily translated to interventions in highly complex real life environments. Agent-based methods on the other hand allow detailed modeling of the environment but optimization is precluded by the large number of parameters. Our goal was to combine the advantages of both approaches, i.e., to allow control optimization in complex environments. The epidemic control objectives are expressed as a time-dependent reference for the number of infected people. To track this reference, a model predictive controller (MPC) is designed with a compartmental ODE prediction model to compute the optimal level of stringency of interventions, which are later translated to specific actions such as mobility restriction, quarantine policy, masking rules, school closure. The effects of interventions on the transmission rate of the pathogen, and hence their stringency, are computed using PanSim, an agent-based epidemic simulator that contains a detailed model of the environment. The realism and practical applicability of the method is demonstrated by the wide range of discrete level measures that can be taken into account. Moreover, the change between measures applied during consecutive planning intervals is also minimized. We found that such a combined intervention planning strategy is able to efficiently control a COVID-19-like epidemic process, in terms of incidence, virulence, and infectiousness with surprisingly sparse (e.g. 21 day) intervention regimes. At the same time, the approach proved to be robust even in scenarios with significant model uncertainties, such as unknown transmission rate, uncertain time and probability constants. The high performance of the computation allows a large number of test cases to be run. The proposed computational framework can be reused for epidemic management of unexpected pandemic events and can be customized to the needs of any country.

Pandemic management requires reliable and efficient dynamical simulation to predict and control disease spreading. The COVID-19 (SARS-CoV-2) pandemic is mitigated by several non-pharmaceutical interventions, but it is hard to predict which of these are the most effective for a given population. We developed the computationally effective and scalable, agent-based microsimulation framework PanSim, allowing us to test control measures in multiple infection waves caused by the spread of a new virus variant in a city-sized societal environment using a unified framework fitted to realistic data. We show that vaccination strategies prioritising occupational risk groups minimise the number of infections but allow higher mortality while prioritising vulnerable groups minimises mortality but implies an increased infection rate. We also found that intensive vaccination along with non-pharmaceutical interventions can substantially suppress the spread of the virus, while low levels of vaccination, premature reopening may easily revert the epidemic to an uncontrolled state. Our analysis highlights that while vaccination protects the elderly from COVID-19, a large percentage of children will contract the virus, and we also show the benefits and limitations of various quarantine and testing scenarios. The uniquely detailed spatio-temporal resolution of PanSim allows the design and testing of complex, specifically targeted interventions with a large number of agents under dynamically changing conditions.

BACKGROUND: The long-term availability of online Web services is of utmost importance to ensure reproducibility of analytical results. However, because of lack of maintenance following acceptance, many servers become unavailable after a short period of time. Our aim was to monitor the accessibility and the decay rate of published Web services as well as to determine the factors underlying trends changes. METHODS: We searched PubMed to identify publications containing Web server-related terms published between 1994 and 2017. Automatic and manual screening was used to check the status of each Web service. Kruskall-Wallis, Mann-Whitney and Chi-square tests were used to evaluate various parameters, including availability, accessibility, platform, origin of authors, citation, journal impact factor and publication year. RESULTS: We identified 3649 publications in 375 journals of which 2522 (69%) were currently active. Over 95% of sites were running in the first 2 years, but this rate dropped to 84% in the third year and gradually sank afterwards (P < 1e-16). The mean half-life of Web services is 10.39 years. Working Web services were published in journals with higher impact factors (P = 4.8e-04). Services published before the year 2000 received minimal attention. The citation of offline services was less than for those online (P = 0.022). The majority of Web services provide analytical tools, and the proportion of databases is slowly decreasing. Conclusions. Almost one-third of Web services published to date went out of service. We recommend continued support of Web-based services to increase the reproducibility of published results.

SUMMARY: The quantification of RNA sequencing (RNA-seq) abundance using a normalization method that calculates transcripts per million (TPM) is a key step to compare multiple samples from different experiments. TPMCalculator is a one-step software to process RNA-seq alignments in BAM format and reports TPM values, raw read counts and feature lengths for genes, transcripts, exons and introns. The program describes the genomic features through a model generated from the gene transfer format file used during alignments reporting of the TPM values and the raw read counts for each feature. In this paper, we show the correlation for 1256 samples from the TCGA-BRCA project between TPM and FPKM reported by TPMCalculator and RSeQC. We also show the correlation for raw read counts reported by TPMCalculator, HTSeq and featureCounts. AVAILABILITY AND IMPLEMENTATION: TPMCalculator is freely available at https://github.com/ncbi/TPMCalculator. It is implemented in C++14 and supported on Mac OS X, Linux and MS Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Bioinformatics (2010) 26(19) 2482–2483 The authors of the above article would like it to be known that the principle of Multi-netclust is incorrectly illustrated in Figure 1. The connected clusters shown in B and C do not correspond with the aggregation rules/formulae indicated below the illustrations. Swapping the clusters with one another restores this correspondence. The authors apologize for this error.

MOTIVATION: Tandem mass spectrometry has become a standard tool for identifying post-translational modifications (PTMs) of proteins. Algorithmic searches for PTMs from tandem mass spectrum data (MS/MS) tend to be hampered by noisy data as well as by a combinatorial explosion of search space. This leads to high uncertainty and long search-execution times. RESULTS: To address this issue, we present PTMTreeSearch, a new algorithm that uses a large database of known PTMs to identify PTMs from MS/MS data. For a given peptide sequence, PTMTreeSearch builds a computational tree wherein each path from the root to the leaves is labeled with the amino acids of a peptide sequence. Branches then represent PTMs. Various empirical tree pruning rules have been designed to decrease the search-execution time by eliminating biologically unlikely solutions. PTMTreeSearch first identifies a relatively small set of high confidence PTM types, and in a second stage, performs a more exhaustive search on this restricted set using relaxed search parameter settings. An analysis of experimental data shows that using the same criteria for false discovery, PTMTreeSearch annotates more peptides than the current state-of-the-art methods and PTM identification algorithms, and achieves this at roughly the same execution time. PTMTreeSearch is implemented as a plugable scoring function in the X!Tandem search engine. AVAILABILITY: The source code of PTMTreeSearch and a demo server application can be found at http://net.icgeb.org/ptmtreesearch

Jingchu Luo is a Professor in the College of Life Sciences and Center for Bioinformatics, Peking University, China. He is the EMBnet China Node manager and a long-term friend of Jack Leunissen. Harm Nijveen is a scientific programmer at Wageningen University and Research Center, the Netherlands. He had been working with Jack Leunissen for several years. Teresa Attwood is a Professor of Bioinformatics in the Faculty of Life Sciences and School of Computer Science at the University of Manchester, UK. She is the current Chair of the EMBnet Executive Board. David Judge is a bioinformatics trainer in Cambridge University and a long-term friend of Jack Leunissen. Sandor Pongor is a Group Leader of Protein Structure and Bioinformatics, the International Center for Genetic Engineering and Biotechnology (ICGEB), Italy. He organized bioinformatics courses every June in ICGEB. David Landsman is Chief of the Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health. Martin Bishop is the Managing Editor of Briefings in Bioinformatics. It has already been a year since Jack Leunissen, a former member of the editorial board of Briefings in Bioinformatics, passed away on 14 May 2012. Professor Dr Jack A.M. Leunissen was one of the pioneers of bioinformatics in the Netherlands, in Europe and around the world. Together with senior members of the European Molecular Biology Network (EMBnet), Jack worked with Henry Stewart Publications to launch this journal in 2000, aiming to publish review articles in bioinformatics to benefit the ever-growing community of bioinformatics researchers. He served as a member of the editorial board for >10 years, devoting much of his time to reviewing manuscripts and providing constructive feedback. Born on 1 August 1954 and educated as a biochemist in the 1980s, Jack showed an interest in bioinformatics early in his scientific career. He created the Biocomputing Environment at the University of Nijmegen in 1982, and his PhD thesis, ‘Computer Applications in Protein and Nucleic Acid Sequence Analysis’ in 1989 was one of the earliest in the biocomputing community. During his PhD studies, Jack started the biocomputing section of the Dutch National academic facility for computer-assisted organic synthesis and modelling and worked there for >10 years. In that period, Jack was also strongly involved in the establishment of EMBnet. He was manager of his country’s node and served as Chairman of the Executive Board of EMBnet from 1999 to 2003. In 2000, he was appointed as senior lecturer in bioinformatics at the Centre for Molecular and Biomolecular Informatics at Nijmegen University. At the end of 2002, he accepted the position of Chair in Bioinformatics at the Department of Plant Sciences of the Wageningen University and Research Center. At the same time, he was involved in the newly formed Netherlands Bioinformatics Centre as project leader, member of the National Advisory Committee and member of the Management Team. Jack had a broad interest in bioinformatics related topics, which he was able to pass on to his PhD and MSc students, working on diverse subjects such as text mining, protein orthology, comparative anatomy, web services and Bayesian networks. His curiosity put him in touch with experts from various related disciplines like computer science, mathematics, statistics and linguistics. Even during the tenure of his professorship, he enjoyed exploring new programming languages and technologies to evaluate their usefulness for bioinformatics. Despite his illness, he continued to be actively involved in the work of his students until the end, including reviewing the article ‘Understanding and Identification of Amino Acid Repeats’ published in this issue by his students. It is hard to overstate the contribution that Jack made to bioinformatics education and training, especially to end users coming from biological backgrounds. From the mid 80s, he taught on numerous courses, workshops and conferences within and outside Europe. Together with other colleagues, he taught on the Bioinformatics summer school at the International Center for Genetic Engineering and Biotechnology in Trieste almost every year from 1993. He was also invited to teach several courses in Peking University, where the Chinese EMBnet node is located. Those he taught will never forget his enthusiasm and inspirational style in the class room. In May 2012, he received a prestigious award from the Dutch industry platform for his activities towards making education and training software and databases more accessible for everybody. Jack, we miss you greatly.

MOTIVATION: Identification of proteins by mass spectrometry-based proteomics requires automated interpretation of peptide tandem mass spectrometry spectra. The effectiveness of peptide identification can be greatly improved by filtering out extraneous noise peaks before the subsequent database searching steps. RESULTS: Here we present a novel chemical rule-based filtering algorithm, termed CRF, which makes use of the predictable patterns (rules) of collision-induced peptide fragmentation. The algorithm selects peak pairs that obey the common fragmentation rules within plausible limits of mass tolerance as well as peak intensity and produces spectra that can be subsequently submitted to any search engine. CRF increases the positive predictive value and decreases the number of random matches and thus improves performance by 15-20% in terms of peptide annotation using search engines, such as X!Tandem. Importantly, the algorithm also achieves data compression rates of ∼75%. AVAILABILITY: The MATLAB source code and a web server are available at http://hydrax.icgeb.trieste.it/CRFilter/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters that are connected in all or in either of the networks. The tool is written in C/C++ and is available either as a form-based or as a command-line-based program running on Linux platforms. The algorithm is fast, processing a network of > 10(6) nodes and 10(8) edges takes only a few minutes on an ordinary computer. AVAILABILITY: http://www.bioinformatics.nl/netclust/.

ROC ('receiver operator characteristics') analysis is a visual as well as numerical method used for assessing the performance of classification algorithms, such as those used for predicting structures and functions from sequence data. This review summarizes the fundamental concepts of ROC analysis and the interpretation of results using examples of sequence and structure comparison. We overview the available programs and provide evaluation guidelines for genomic/proteomic data, with particular regard to applications to large and heterogeneous databases used in bioinformatics.

Abstract Summary: PRIDE-NMR is a fast novel method to relate known protein folds to NMR distance restraints. It can be used to obtain a first guess about a structure being determined, as well as to estimate the completeness or verify the correctness of NOE data. Availability: The PRIDE-NMR server is available at http://www.icgeb.org/pride Contact: [email protected] Supplementary information: Description of the server and details of the tests presented can be found at http://www.icgeb.org/pride

MOTIVATION: Likelihood ratio approximants (LRA) have been widely used for model comparison in statistics. The present study was undertaken in order to explore their utility as a scoring (ranking) function in the classification of protein sequences. RESULTS: We used a simple LRA-based on the maximal similarity (or minimal distance) scores of the two top ranking sequence classes. The scoring methods (Smith-Waterman, BLAST, local alignment kernel and compression based distances) were compared on datasets designed to test sequence similarities between proteins distantly related in terms of structure or evolution. It was found that LRA-based scoring can significantly outperform simple scoring methods.

MOTIVATION: Distance measures built on the notion of text compression have been used for the comparison and classification of entire genomes and mitochondrial genomes. The present study was undertaken in order to explore their utility in the classification of protein sequences. RESULTS: We constructed compression-based distance measures (CBMs) using the Lempel-Zlv and the PPMZ compression algorithms and compared their performance with that of the Smith-Waterman algorithm and BLAST, using nearest neighbour or support vector machine classification schemes. The datasets included a subset of the SCOP protein structure database to test distant protein similarities, a 3-phosphoglycerate-kinase sequences selected from archaean, bacterial and eukaryotic species as well as low and high-complexity sequence segments of the human proteome, CBMs values show a dependence on the length and the complexity of the sequences compared. In classification tasks CBMs performed especially well on distantly related proteins where the performance of a combined measure, constructed from a CBM and a BLAST score, approached or even slightly exceeded that of the Smith-Waterman algorithm and two hidden Markov model-based algorithms.

UNLABELLED: An improved version of the PRIDE (PRobaility of IDEntity) fold prediction algorithm has been developed, based on more solid statistical basis, fast search capabilities and efficient input structure processing. The new algorithm is effective in identifying protein structures at the 'H' level of the CATH hierarchy. AVAILABILITY: The new algorithm is integrated into the PRIDE2 web servers at http://pride.szbk.u-szeged.hu and http://www.icgeb.org/pride. SUPPLEMENTARY INFORMATION: Detailed documentation and performance evaluation is available in the description section of the PRIDE2 web server.

BACKGROUND: The process of oxidative folding combines the formation of native disulfide bond with conformational folding resulting in the native three-dimensional fold. Oxidative folding pathways can be described in terms of disulfide intermediate species (DIS) which can also be isolated and characterized. Each DIS corresponds to a family of folding states (conformations) that the given DIS can adopt in three dimensions. RESULTS: The oxidative folding space can be represented as a network of DIS states interconnected by disulfide interchange reactions that can either create/abolish or rearrange disulfide bridges. We propose a simple 3D representation wherein the states having the same number of disulfide bridges are placed on separate planes. In this representation, the shuffling transitions are within the planes, and the redox edges connect adjacent planes. In a number of experimentally studied cases (bovine pancreatic trypsin inhibitor, insulin-like growth factor and epidermal growth factor), the observed intermediates appear as part of contiguous oxidative folding pathways. CONCLUSIONS: Such networks can be used to visualize folding pathways in terms of the experimentally observed intermediates. A simple visualization template written for the Tulip package http://www.tulip-software.org/ can be obtained from V.A.

Abstract Summary: A web server has been established for the statistical evaluation of introns in various taxonomic groups and the comparison of taxonomic groups in terms of intron type, length, base composition, etc. The options include the graphic analysis of splice sites and a probability test for exon-shuffling within the selected group. Availability: introns.abc.hu, http://www.icgeb.trieste.it/introns Contact: [email protected]@[email protected] * To whom correspondence should be addressed.

SUMMARY: In order to obtain an accurate description of the protein interior, we describe a simple and fast algorithm that measures the depth of each atom in a protein (dpx), defined as its distance (A) from the closest solvent accessible atom. The program reads a PDB file containing the atomic solvent accessibility in the B-factor field, and writes a file in the same format, where the B-factor field now contains the dpx value. Output structure files can be thus directly displayed with molecular graphics programs like RASMOL, MOLMOL, Swiss-PDB View and colored according to dpx values. AVAILABILITY: The algorithm is implemented in a standalone program written in C and its source is freely available at ftp.icgeb.trieste.it/pub/DPX or on request from the authors.

MOTIVATION: A simple and fast algorithm is described that calculates a measure of protrusion (cx) for atoms in protein structures, directly useable with the common molecular graphics programs. RESULTS: A sphere of predetermined radius is centered around each non-hydrogen atom, and the volume occupied by the protein and the free volume within the sphere (internal and external volumes, respectively) are calculated. Atoms in protruding regions have a high ratio (cx) between the external and the internal volume. The program reads a PDB file, and writes the output in the same format, with cx values in the B factor field. Output structure files can be directly displayed with standard molecular graphics programs like RASMOL, MOLMOL, Swiss-PDB Viewer and colored according to cx values. We show the potential use of this program in the analysis of two protein-protein complexes and in the prediction of limited proteolysis sites in native proteins. AVAILABILITY: The algorithm is implemented in a standalone program written in C and its source is freely available at ftp.icgeb.trieste.it/pub/CX or on request from the authors.

Abstract Summary: A simple heuristic scoring method is described for assigning sequences to known domain types based on BLAST search outputs. The scoring is based on the score distribution of the known domain groups determined from a database versus database comparison and is directly applicable to BLAST output processing. Availability: The scoring system will be incorporated into the server www.icgeb.trieste.it/sbase/ Contact: [email protected]; [email protected]

UNLABELLED: A WWW server is described for creating 3D models of canonical or bent DNA starting from sequence data. Predicted DNA trajectory is first computed based on a choice of di- and tri-nucleotide models (M.G. Munteanu et al., Trends Biochem. Sci. 23, 341-347, 1998); an atomic model is then constructed and optionally energy-minimized with constrained molecular dynamics. The data are presented as a standard PDB file, directly viewable on the user's PC using any molecule manipulation program. AVAILABILITY: The model.it server is freely available at http://www.icgeb.trieste.it/dna/ CONTACT: [email protected]; [email protected] SUPPLEMENTARY INFORMATION: a series of help files is available at the above address.

RESULTS: A WWW server for protein domain homology prediction, based on BLAST search and a simple data-mining algorithm (Hegyi,H. and Pongor,S. (1993) Comput. Appl. Biosci., 9, 371-372), was constructed providing a tabulated list and a graphic plot of similarities. AVAILABILITY: http://www.icgeb.trieste.it/domain. Mirror site is available at http://sbase.abc.hu/domain. A standalone programme will be available on request. SUPPLEMENTARY INFORMATION: A series of help files is available at the above addresses.

Hedvig Hegyi, Sándor Pongor; Predicting potential domain homologies from FASTA search results, Bioinformatics, Volume 9, Issue 3, 1 June 1993, Pages 371–372, ht