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December 2013

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases
Xie, C; Mao, XZ; Huang, JJ; Ding, Y; Wu, JM; Dong, S; Kong, L; Gao, G; Li, CY; Wei, LP
Nucleic Acids Res. (2011) 39 (suppl_2): W316-W322
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High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at

HMMER web server: interactive sequence similarity searching
Finn, RD; Clements, J; Eddy, SR
Nucleic Acids Res. (2011) 39 (suppl_2): W29-W37
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HMMER is a software suite for protein sequence similarity searches using probabilistic methods. Previously, HMMER has mainly been available only as a computationally intensive UNIX command-line tool, restricting its use. Recent advances in the software, HMMER3, have resulted in a 100-fold speed gain relative to previous versions. It is now feasible to make efficient profile hidden Markov model (profile HMM) searches via the web. A HMMER web server ( has been designed and implemented such that most protein database searches return within a few seconds. Methods are available for searching either a single protein sequence, multiple protein sequence alignment or profile HMM against a target sequence database, and for searching a protein sequence against Pfam. The web server is designed to cater to a range of different user expertise and accepts batch uploading of multiple queries at once. All search methods are also available as RESTful web services, thereby allowing them to be readily integrated as remotely executed tasks in locally scripted workflows. We have focused on minimizing search times and the ability to rapidly display tabular results, regardless of the number of matches found...

MetaboAnalyst 2.0--a comprehensive server for metabolomic data analysis
Xia, JG; Mandal, R; Sinelnikov, IV; Broadhurst, D; Wishart, DS
Nucleic Acids Res. (2012) 40 (suppl_2): W127-W133
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First released in 2009, MetaboAnalyst ( was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms...

antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences
Medema, MH; Blin, K; Cimermancic, P; de Jager, V; Zakrzewski, P; Fischbach, MA; Weber, T; Takano, E; Breitling, R
Nucleic Acids Res. (2011) 39 (suppl_2): W339-W346
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Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs. To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes. However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources. Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins...

RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics
Lohse, M; Bolger, AM; Nagel, A; Fernie, AR; Lunn, JE; Stitt, M; Usadel, B
Nucleic Acids Res. (2012) 40 (suppl_2): W622-W627
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Recent rapid advances in next generation RNA sequencing (RNA-Seq)-based provide researchers with unprecedentedly large data sets and open new perspectives in transcriptomics. Furthermore, RNA-Seq-based transcript profiling can be applied to non-model and newly discovered organisms because it does not require a predefined measuring platform (like e.g. microarrays). However, these novel technologies pose new challenges: the raw data need to be rigorously quality checked and filtered prior to analysis, and proper statistical methods have to be applied to extract biologically relevant information. Given the sheer volume of data, this is no trivial task and requires a combination of considerable technical resources along with bioinformatics expertise. To aid the individual researcher, we have developed RobiNA as an integrated solution that consolidates all steps of RNA-Seq-based differential gene-expression analysis in one user-friendly cross-platform application featuring a rich graphical user interface. RobiNA accepts raw FastQ files, SAM/BAM alignment files and counts tables as input...

ncFANs: a web server for functional annotation of long non-coding RNAs
Liao, Q; Xiao, H; Bu, DC; Xie, CY; Miao, RY; Luo, HT; Zhao, GG; Yu, KT; Zhao, HT; Skogerbo, G; Chen, RS; Wu, ZD; Liu, CN; Zhao, Y
Nucleic Acids Res. (2011) 39 (suppl_2): W118-W124
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Recent interest in the non-coding transcriptome has resulted in the identification of large numbers of long non-coding RNAs (lncRNAs) in mammalian genomes, most of which have not been functionally characterized. Computational exploration of the potential functions of these lncRNAs will therefore facilitate further work in this field of research. We have developed a practical and user-friendly web interface called ncFANs (non-coding RNA Function ANnotation server), which is the first web service for functional annotation of human and mouse lncRNAs. On the basis of the re-annotated Affymetrix microarray data, ncFANs provides two alternative strategies for lncRNA functional annotation: one utilizing three aspects of a coding-non-coding gene co-expression (CNC) network, the other identifying condition-related differentially expressed lncRNAs. ncFANs introduces a highly efficient way of re-using the abundant pre-existing microarray data. The present version of ncFANs includes re-annotated CDF files for 10 human and mouse Affymetrix microarrays...

A decade of web server updates at the bioinformatics links directory: 2003-2012
Brazas, MD; Yim, D; Yeung, W; Ouellette, BFF
Nucleic Acids Res. (2012) 40 (suppl_2): W3-W12
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The 2012 Bioinformatics Links Directory update marks the 10th special Web Server issue from Nucleic Acids Research. Beginning with content from their 2003 publication, the Bioinformatics Links Directory in collaboration with Nucleic Acids Research has compiled and published a comprehensive list of freely accessible, online tools, databases and resource materials for the bioinformatics and life science research communities. The past decade has exhibited significant growth and change in the types of tools, databases and resources being put forth, reflecting both technology changes and the nature of research over that time. With the addition of 90 web server tools and 12 updates from the July 2012 Web Server issue of Nucleic Acids Research, the Bioinformatics Links Directory at now contains an impressive 134 resources, 455 databases and 1205 web server tools, mirroring the continued activity and efforts of our field.

iPBA: a tool for protein structure comparison using sequence alignment strategies
Gelly, JC; Joseph, AP; Srinivasan, N; de Brevern, AG
Nucleic Acids Res. (2011) 39 (suppl_2): W18-W23
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With the immense growth in the number of available protein structures, fast and accurate structure comparison has been essential. We propose an efficient method for structure comparison, based on a structural alphabet. Protein Blocks (PBs) is a widely used structural alphabet with 16 pentapeptide conformations that can fairly approximate a complete protein chain. Thus a 3D structure can be translated into a 1D sequence of PBs. With a simple Needleman-Wunsch approach and a raw PB substitution matrix, PB-based structural alignments were better than many popular methods. iPBA web server presents an improved alignment approach using (i) specialized PB Substitution Matrices (SM) and (ii) anchor-based alignment methodology. With these developments, the quality of similar to 88% of alignments was improved. iPBA alignments were also better than DALI, MUSTANG and GANGSTA(+) in > 80% of the cases. The webserver is designed to for both pairwise comparisons and database searches. Outputs are given as sequence alignment and superposed 3D structures displayed using PyMol and Jmol. A local alignment option for detecting subs-structural similarity is also embedded...

R.E.D. Server: a web service for deriving RESP and ESP charges and building force field libraries for new molecules and molecular fragments
Vanquelef, E; Simon, S; Marquant, G; Garcia, E; Klimerak, G; Delepine, JC; Cieplak, P; Dupradeau, FY
Nucleic Acids Res. (2011) 39 (suppl_2): W511-W517
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R.E.D. Server is a unique, open web service, designed to derive non-polarizable RESP and ESP charges and to build force field libraries for new molecules/molecular fragments. It provides to computational biologists the means to derive rigorously molecular electrostatic potential-based charges embedded in force field libraries that are ready to be used in force field development, charge validation and molecular dynamics simulations. R.E.D. Server interfaces quantum mechanics programs, the RESP program and the latest version of the R.E.D. tools. A two step approach has been developed. The first one consists of preparing P2N file(s) to rigorously define key elements such as atom names, topology and chemical equivalencing needed when building a force field library. Then, P2N files are used to derive RESP or ESP charges embedded in force field libraries in the Tripos mol2 format. In complex cases an entire set of force field libraries or force field topology database is generated...

GENIES: gene network inference engine based on supervised analysis
Kotera, M; Yamanishi, Y; Moriya, Y; Kanehisa, M; Goto, S
Nucleic Acids Res. (2012) 40 (W1): W162-W167
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Gene network inference engine based on supervised analysis (GENIES) is a web server to predict unknown part of gene network from various types of genome-wide data in the framework of supervised network inference. The originality of GENIES lies in the construction of a predictive model using partially known network information and in the integration of heterogeneous data with kernel methods. The GENIES server accepts any 'profiles' of genes or proteins (e.g. gene expression profiles, protein subcellular localization profiles and phylogenetic profiles) or pre-calculated gene-gene similarity matrices (or 'kernels') in the tab-delimited file format. As a training data set to learn a predictive model, the users can choose either known molecular network information in the KEGG PATHWAY database or their own gene network data. The user can also select an algorithm of supervised network inference, choose various parameters in the method, and control the weights of heterogeneous data integration. The server provides the list of newly predicted gene pairs, maps the predicted gene pairs onto the associated pathway diagrams in KEGG PATHWAY and indicates candidate genes for missing enzymes...

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