Bioinformatics Meets Virology: The European Virus Bioinformatics Center’s Second Annual Meeting

The Second Annual Meeting of the European Virus Bioinformatics Center (EVBC), held in Utrecht, Netherlands, focused on computational approaches in virology, with topics including (but not limited to) virus discovery, diagnostics, (meta-)genomics, modeling, epidemiology, molecular structure, evolution, and viral ecology. The goals of the Second Annual Meeting were threefold: (i) to bring together virologists and bioinformaticians from across the academic, industrial, professional, and training sectors to share best practice; (ii) to provide a meaningful and interactive scientific environment to promote discussion and collaboration between students, postdoctoral fellows, and both new and established investigators; (iii) to inspire and suggest new research directions and questions. Approximately 120 researchers from around the world attended the Second Annual Meeting of the EVBC this year, including 15 renowned international speakers. This report presents an overview of new developments and novel research findings that emerged during the meeting.

[1]  Martin Beer,et al.  A new era of virus bioinformatics. , 2018, Virus research.

[2]  Tatsuya Akutsu,et al.  Network controllability: viruses are driver agents in dynamic molecular systems , 2018, bioRxiv.

[3]  H. Neve,et al.  Rates of Mutation and Recombination in Siphoviridae Phage Genome Evolution over Three Decades , 2018, Molecular biology and evolution.

[4]  Philippe Le Mercier,et al.  Virologists—Heroes need weapons , 2018, PLoS pathogens.

[5]  E. Koonin,et al.  Metagenomics reshapes the concepts of RNA virus evolution by revealing extensive horizontal virus transfer , 2017, Virus Research.

[6]  A. Mchardy,et al.  In Silico Vaccine Strain Prediction for Human Influenza Viruses. , 2017, Trends in microbiology.

[7]  Robert A Edwards,et al.  Discovery of an expansive bacteriophage family that includes the most abundant viruses from the human gut , 2017, Nature Microbiology.

[8]  Alejandro Reyes,et al.  Use of profile hidden Markov models in viral discovery: current insights , 2017 .

[9]  Jonathan Vincent,et al.  WIsH: who is the host? Predicting prokaryotic hosts from metagenomic phage contigs , 2017, Bioinform..

[10]  Itai Sharon,et al.  Novel Abundant Oceanic Viruses of Uncultured Marine Group II Euryarchaeota , 2017, Current Biology.

[11]  Natalia N. Ivanova,et al.  Giant viruses with an expanded complement of translation system components , 2017, Science.

[12]  Yuelong Shu,et al.  GISAID: Global initiative on sharing all influenza data – from vision to reality , 2017, Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin.

[13]  F. Klawonn,et al.  Sweep Dynamics (SD) plots: Computational identification of selective sweeps to monitor the adaptation of influenza A viruses , 2017, Scientific Reports.

[14]  Jie Ren,et al.  Alignment-free \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$d_2^*$\end{document} oligonucleotide frequency dissi , 2016, Nucleic acids research.

[15]  Andrew J. Davison,et al.  Consensus statement: Virus taxonomy in the age of metagenomics , 2017, Nature Reviews Microbiology.

[16]  M. Sullivan,et al.  Phages rarely encode antibiotic resistance genes: a cautionary tale for virome analyses , 2016, The ISME Journal.

[17]  A. Drummond,et al.  Inferring Ancestral Recombination Graphs from Bacterial Genomic Data , 2016, Genetics.

[18]  Aldert L. Zomer,et al.  Transcriptome assists prognosis of disease severity in respiratory syncytial virus infected infants , 2016, Scientific Reports.

[19]  Rob J. De Boer,et al.  RTCR: a pipeline for complete and accurate recovery of T cell repertoires from high throughput sequencing data , 2016, Bioinform..

[20]  François Balloux,et al.  Inferences from tip‐calibrated phylogenies: a review and a practical guide , 2016, Molecular ecology.

[21]  A. Gruber,et al.  GenSeed-HMM: A Tool for Progressive Assembly Using Profile HMMs as Seeds and its Application in Alpavirinae Viral Discovery from Metagenomic Data , 2016, Front. Microbiol..

[22]  Alexandra J. Lee,et al.  Genetic changes found in a distinct clade of Enterovirus D68 associated with paralysis during the 2014 outbreak , 2016, Virus evolution.

[23]  A. Mchardy,et al.  Determination of antigenicity-altering patches on the major surface protein of human influenza A/H3N2 viruses , 2016, Virus evolution.

[24]  O. Pybus,et al.  Measurably evolving pathogens in the genomic era. , 2015, Trends in ecology & evolution.

[25]  Matthew B. Sullivan,et al.  VirSorter: mining viral signal from microbial genomic data , 2015, PeerJ.

[26]  David L. Robertson,et al.  A logical model of HIV-1 interactions with the T-cell activation signalling pathway , 2015, Bioinform..

[27]  Daniel J. Wilson,et al.  ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes , 2015, PLoS Comput. Biol..

[28]  Jacqueline A. Keane,et al.  Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins , 2014, Nucleic acids research.

[29]  A. Mchardy,et al.  Computational Prediction of Vaccine Strains for Human Influenza A (H3N2) Viruses , 2014, Journal of Virology.

[30]  R. Edwards,et al.  A highly abundant bacteriophage discovered in the unknown sequences of human faecal metagenomes , 2014, Nature Communications.

[31]  Dong Xie,et al.  BEAST 2: A Software Platform for Bayesian Evolutionary Analysis , 2014, PLoS Comput. Biol..

[32]  François Enault,et al.  Assessment of viral community functional potential from viral metagenomes may be hampered by contamination with cellular sequences , 2013, Open Biology.

[33]  Alice Carolyn McHardy,et al.  Inference of Genotype–Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses , 2012, PLoS Comput. Biol..

[34]  J. Burton,et al.  Rapid Pneumococcal Evolution in Response to Clinical Interventions , 2011, Science.

[35]  Alice Carolyn McHardy,et al.  Allele dynamics plots for the study of evolutionary dynamics in viral populations , 2010, Nucleic Acids Res..

[36]  David L. Robertson,et al.  Patterns of HIV-1 Protein Interaction Identify Perturbed Host-Cellular Subsystems , 2010, PLoS Comput. Biol..

[37]  David L. Robertson,et al.  The biological context of HIV-1 host interactions reveals subtle insights into a system hijack , 2010, BMC Systems Biology.

[38]  David L Robertson,et al.  Cataloguing the HIV type 1 human protein interaction network. , 2008, AIDS research and human retroviruses.