Steven Maere

Bio: Steven Maere is an academic researcher from Ghent University. The author has contributed to research in topics: Gene family & Paleopolyploidy. The author has an hindex of 37, co-authored 57 publications receiving 12366 citations. Previous affiliations of Steven Maere include Flanders Institute for Biotechnology & University of California, San Diego.

BiNGO : a Cytoscape plugin to assess overrepresentation of Gene Ontology categories in Biological Networks

Abstract: Summary: The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape's versatile visualization environment to produce an intuitive and customizable visual representation of the results. Availability: http://www.psb.ugent.be/cbd/papers/BiNGO/ Contact: martin.kuiper@psb.ugent.be

Integration of biological networks and gene expression data using Cytoscape

Abstract: Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

The evolutionary significance of ancient genome duplications

Abstract: Many organisms are currently polyploid, or have a polyploid ancestry and now have secondarily 'diploidized' genomes. This finding is surprising because retained whole-genome duplications (WGDs) are exceedingly rare, suggesting that polyploidy is usually an evolutionary dead end. We argue that ancient genome doublings could probably have survived only under very specific conditions, but that, whenever established, they might have had a pronounced impact on species diversification, and led to an increase in biological complexity and the origin of evolutionary novelties.

Modeling gene and genome duplications in eukaryotes.

Abstract: Recent analysis of complete eukaryotic genome sequences has revealed that gene duplication has been rampant. Moreover, next to a continuous mode of gene duplication, in many eukaryotic organisms the complete genome has been duplicated in their evolutionary past. Such large-scale gene duplication events have been associated with important evolutionary transitions or major leaps in development and adaptive radiations of species. Here, we present an evolutionary model that simulates the duplication dynamics of genes, considering genome-wide duplication events and a continuous mode of gene duplication. Modeling the evolution of the different functional categories of genes assesses the importance of different duplication events for gene families involved in specific functions or processes. By applying our model to the Arabidopsis genome, for which there is compelling evidence for three whole-genome duplications, we show that gene loss is strikingly different for large-scale and small-scale duplication events and highly biased toward certain functional classes. We provide evidence that some categories of genes were almost exclusively expanded through large-scale gene duplication events. In particular, we show that the three whole-genome duplications in Arabidopsis have been directly responsible for >90% of the increase in transcription factors, signal transducers, and developmental genes in the last 350 million years. Our evolutionary model is widely applicable and can be used to evaluate different assumptions regarding small- or large-scale gene duplication events in eukaryotic genomes.

Plants with double genomes might have had a better chance to survive the Cretaceous-Tertiary extinction event.

Abstract: Mostflowering plants have been shown to be ancient polyploids that have undergone one or more whole genome duplications early in their evolution. Furthermore, many different plant lineages seem to have experienced an additional, more recent genome duplication. Starting from paralogous genes lying in duplicated segments or identified in large expressed sequence tag collections, we dated these youngest duplication events through penalized likelihood phylogenetic tree inference. We show that a majority of these independent genome duplications are clustered in time and seem to coincide with the Cretaceous‐Tertiary (KT) boundary. The KT extinction event is the most recent mass extinction caused by one or more catastrophic events such as a massive asteroid impact and/or increasedvolcanicactivity.Theseeventsarebelievedtohavegenerated global wildfires and dust clouds that cut off sunlight during long periods of time resulting in the extinction of 60% of plant species, as well as a majority of animals, including dinosaurs. Recent studies suggest that polyploid species can have a higher adaptability and increased tolerance to different environmental conditions. We propose that polyploidization may have contributed to the survival and propagation of several plant lineages during or following the KT extinction event. Due to advantages such as altered gene expression leading to hybrid vigor and an increased set of genes and alleles available for selection, polyploid plants might have been better able to adapt to the drastically changed environment 65 million years ago. angiosperms eudicots Cretaceous–Tertiary boundary penalized likelihood polyploidy

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Abstract: Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Abstract: Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible.

Abstract: A system-wide understanding of cellular function requires knowledge of all functional interactions between the expressed proteins. The STRING database aims to collect and integrate this information, by consolidating known and predicted protein-protein association data for a large number of organisms. The associations in STRING include direct (physical) interactions, as well as indirect (functional) interactions, as long as both are specific and biologically meaningful. Apart from collecting and reassessing available experimental data on protein-protein interactions, and importing known pathways and protein complexes from curated databases, interaction predictions are derived from the following sources: (i) systematic co-expression analysis, (ii) detection of shared selective signals across genomes, (iii) automated text-mining of the scientific literature and (iv) computational transfer of interaction knowledge between organisms based on gene orthology. In the latest version 10.5 of STRING, the biggest changes are concerned with data dissemination: the web frontend has been completely redesigned to reduce dependency on outdated browser technologies, and the database can now also be queried from inside the popular Cytoscape software framework. Further improvements include automated background analysis of user inputs for functional enrichments, and streamlined download options. The STRING resource is available online, at http://string-db.org/.

REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms

Abstract: Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus difficult to interpret. REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures. Furthermore, REVIGO visualizes this non-redundant GO term set in multiple ways to assist in interpretation: multidimensional scaling and graph-based visualizations accurately render the subdivisions and the semantic relationships in the data, while treemaps and tag clouds are also offered as alternative views. REVIGO is freely available at http://revigo.irb.hr/.