Taxonomic analysis of microbial communities is well supported at the level of species and strains. However, species can contain significant phenotypic diversity and strains are rarely widely shared across global populations. Stratifying the diversity between species and strains can identify "subspecies", which are a useful intermediary. High-throughput identification and profiling of subspecies is not yet supported in the microbiome field. Here, we use an operational definition of subspecies based on SNV patterns within species to identify and profile subspecies in metagenomes, along with their distinctive SNVs and genes. We incorporate this method into metaSNV v2, which extends existing SNV-calling software to support further SNV interpretation for population genetics. These new features support microbiome analyses to link SNV profiles with host phenotype or environment and niche-specificity. We demonstrate subspecies identification in marine and faecal metagenomes. In the latter, we analyse 70 species in 7,524 adult and infant subjects, supporting a common subspecies population structure in the human gut microbiome and illustrating some limits in subspecies calling.

Untargeted mass spectrometry is a powerful method for detecting metabolites in biological samples. However, fast and accurate identification of the metabolites' structures from MS/MS spectra is still a great challenge.

The rapidly expanding microbiomics field is generating increasingly larger datasets, characterizing the microbiota in diverse environments. Although classical numerical ecology methods provide a robust statistical framework for their analysis, software currently available is inadequate for large datasets and some computationally intensive tasks, like rarefaction and associated analysis.

Data on bioactivities of drug-like chemicals is rapidly accumulating in public repositories, creating new opportunities for research in computational systems pharmacology. However, integrative analysis of these data sets is difficult due to prevailing ambiguity between chemical names and identifiers and a lack of cross-references between databases.

MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assignments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes.

SUMMARY: Drug versus Disease (DvD) provides a pipeline, available through R or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray repositories. Negatively correlated profiles can be used to generate hypotheses of drug-repurposing whilst positively correlated profiles may be used to infer side-effects of drugs. DvD allows users to compare drug and disease signatures with dynamic access to databases Array Express, GEO and data from the Connectivity Map.Availability and Implementation: R package (submitted to Bioconductor) under GPL 3 and Cytoscape plug-in freely available for download at www.ebi.ac.uk/saezrodriguez/DVD/ CONTACT: saezrodriguez@ebi.ac.uk SUPPLEMENTARY INFORMATION: Accompanies this paper.

SUMMARY: SmashCommunity is a stand-alone metagenomic annotation and analysis pipeline suitable for data from Sanger and 454 sequencing technologies. It supports state-of-the-art software for essential metagenomic tasks such as assembly and gene prediction. It provides tools to estimate the quantitative phylogenetic and functional compositions of metagenomes, to compare compositions of multiple metagenomes and to produce intuitive visual representations of such analyses. AVAILABILITY: SmashCommunity is freely available at http://www.bork.embl.de/software/smash CONTACT: bork@embl.de.

SUMMARY: Recent advances in single-cell manipulation technology, whole genome amplification and high-throughput sequencing have now made it possible to sequence the genome of an individual cell. The bioinformatic analysis of these genomes however is far more complicated than the analysis of those generated using traditional, culture-based methods. In order to simplify this analysis we have developed SmashCell (Simple Metagenomics Analysis SHell-for sequences from single Cells). It is designed to automate the main steps in microbial genome analysis - assembly, gene prediction, functional annotation - in a way that allows parameter and algorithm exploration at each step in the process. It alsomanages the data created by these analyses and provides visualisation methods to allow rapid analysis of the results. AVAILABILITY: The SmashCell source code and a comprehensive manual are available at http://asiago.stanford.edu/SmashCell CONTACT: eoghanh@stanford.edu.

SUMMARY: Multiple Sequence Alignment (MSA) is a central tool in most modern biology studies. However, despite generations of valuable tools, human experts are still able to improve automatically generated MSAs. In an effort to automatically identify the most reliable MSA for a given protein family, we propose a very simple protocol, named AQUA for "Automated quality improvement for multiple sequence alignments". Our current implementation relies on 2 alignment programs (MUSCLE and MAFFT), one refinement program (RASCAL) and one assessment program (NORMD) but other programs could be incorporated at any of the 3 steps. AVAILABILITY: AQUA is implemented in Tcl/Tk and runs in command line on all platforms. The source code is available under the GNU GPL license. Source code, README and Supplementary data are available at http://www.bork.embl.de/Docu/AQUA. CONTACT: muller@embl.de, bork@embl.de.

SUMMARY: Sircah is a flexible tool for the detection, analysis and visualisation of alternative transcripts. It takes as input gene models or spliced alignments and creates a database of alternative transcription events: alternative transcription initiation and polyadenylation, alternative 3' and 5' splice-site usage, skipped exons and retained introns. The results can be visualised in a variety of ways, allowing the creation of publication quality images. RESULTS: AVAILABILITY: The Sircah is available for download under a creative commons license along with additional documentation and a tutorial from http://www.bork.embl.de/Sircah. CONTACT: bork@embl.de.

SUMMARY: Interactive Tree Of Life (iTOL) is a web based tool for the display, manipulation and annotation of phylogenetic trees. Trees can be interactively pruned and re-rooted. Various types of data such as genome sizes or protein domain repertoires can be mapped onto the tree. Export to several bitmap and vector graphics formats is supported. AVAILABILITY: iTOL is available through WWW at http://itol.embl.de.

MOTIVATION: We have previously developed a rule based approach for extracting information on the regulation of gene expression in yeast. The biomedical literature, however, contains information on several other equally important regulatory mechanisms, in particular phosphorylation, which we now expanded our rule based system to also extract. RESULTS: This paper presents new results for extraction of relational information from biomedical text. We have improved our system, STRING-IE, to both capture new types of linguistic constructs as well as new types of biological information (i.e. (de-)phosphorylation). The precision remains stable with a slight increase in recall. From almost one million PubMed abstracts related to four model organisms, we manage to extract regulatory networks and binary phosphorylations comprising 3319 relation chunks. The accuracy is 83-90% and 86-95% for gene expression and (de-)phosphorylation relations, respectively. To achieve this, we made use of an organism-specific resource of gene/protein names considerably larger than those used in most other biology related information extraction approaches. These names were included in the lexicon when retraining the part-of-speech tagger on the GENIA corpus. For the domain in question an accuracy of 96.4% was attained on POS-tags. It should be noted that the rules were developed for yeast and successfully applied to both abstracts and full-text articles related to other organisms with comparable accuracy. AVAILABILITY: The revised GENIA corpus, the POS-tagger, the extraction rules, and the full sets of extracted relations are available from http://www.bork.embl.de/Docu/STRING-IE.

MOTIVATION: Generation of alternative transcripts from the same gene in is an important biological event due to their contribution in creating functional diversity in eukaryotes. In this work, we choose the task of extracting information around this complex topic using a two step procedure involving machine learning and information extraction. RESULTS: In the first step, we trained a classifier that inductively learns to identify sentences about physiological transcript diversity from the MEDLINE abstracts. Using a large hand-built corpus, we compared the sentence classification performance of various text categorization methods. Support vector machines (SVM) followed by the maximum entropy classifier outperformed other methods for the sentence classification task. The SVM with the radial basis function kernel and optimized parameters achieved Fbeta-measure of 91% during the four-fold cross validation and of 74% when applied to all sentences in more than 12 million abstracts of MEDLINE. In the second step, we identified eight frequently present semantic categories in the sentences and performed a limited amount of semantic role labeling. The role labeling step also achieved very high Fbeta-measure for all eight categories. AVAILABILITY: The results of our two-step procedure are summarized in the LSAT database of alternative transcripts. LSAT is available at http://www.bork.embl.de/LSAT/.

MOTIVATION: The hypersensitive response (HR) is a process activated by plants after microbial infection. Its main phenotypic effects are both a programmed death of the plant cells near the infection site and a reduction of the microbial proliferation. Although many resistance genes (R genes) associated to HR have been identified, very little is known about the molecular mechanisms activated after their expression. RESULTS: The analysis of the product of one of the R genes, the Hin1 protein, led to the identification of a novel domain, which we named WHy because it is detectable in proteins involved in Water stress and Hypersensitive response. The expression of this domain during both biotic infection and response to desiccation points to a molecular machinery common to these two stress conditions. Moreover, its presence in a restricted number of bacteria suggests a possible use for marking plant pathogenicity. CONTACT: francesca.ciccarelli@embl.de SUPPLEMENTARY INFORMATION: Supplementary data (Figures S1 and S2 and Table S1) and the alignment in clustal format are available at http://www.bork.embl.de/~ciccarel/WHy_add_data.html.

MOTIVATION: DNA microarrays have been used extensively to study the cell cycle transcription programme in a number of model organisms. The Saccharomyces cerevisiae data in particular have been subjected to a wide range of bioinformatics analysis methods, aimed at identifying the correct and complete set of periodically expressed genes. RESULTS: Here, we provide the first thorough benchmark of such methods, surprisingly revealing that most new and more mathematically advanced methods actually perform worse than the analysis published with the original microarray data sets. We show that this loss of accuracy specifically affects methods that only model the shape of the expression profile without taking into account the magnitude of regulation. We present a simple permutation-based method that performs better than most existing methods.

SUMMARY: Medusa is a java application for visualizing and manipulating graphs of interaction, such as data from the STRING database. It features an intuitive user interface developed with the help of biologists. Medusa is optimized for accessing protein interaction data from STRING, but can be used for any type of graph from any scientific field. AVAILABILITY: Medusa, along with sample data sets and instructions, can be downloaded from http://www.bork.embl.de/medusa.

SUMMARY: The Helmholtz Network for Bioinformatics (HNB) is a joint venture of eleven German bioinformatics research groups that offers convenient access to numerous bioinformatics resources through a single web portal. The 'Guided Solution Finder' which is available through the HNB portal helps users to locate the appropriate resources to answer their queries by employing a detailed, tree-like questionnaire. Furthermore, automated complex tool cascades ('tasks'), involving resources located on different servers, have been implemented, allowing users to perform comprehensive data analyses without the requirement of further manual intervention for data transfer and re-formatting. Currently, automated cascades for the analysis of regulatory DNA segments as well as for the prediction of protein functional properties are provided. AVAILABILITY: The HNB portal is available at http://www.hnbioinfo.de

MOTIVATION: The description of genes in databases by keywords helps the non-specialist to quickly grasp the properties of a gene and increases the efficiency of computational tools that are applied to gene data (e.g. searching a gene database for sequences related to a particular biological process). However, the association of keywords to genes or protein sequences is a difficult process that ultimately implies examination of the literature related to a gene. RESULTS: To support this task, we present a procedure to derive keywords from the set of scientific abstracts related to a gene. Our system is based on the automated extraction of mappings between related terms from different databases using a model of fuzzy associations that can be applied with all generality to any pair of linked databases. We tested the system by annotating genes of the SWISS-PROT database with keywords derived from the abstracts linked to their entries (stored in the MEDLINE database of scientific references). The performance of the annotation procedure was much better for SWISS-PROT keywords (recall of 47%, precision of 68%) than for Gene Ontology terms (recall of 8%, precision of 67%). AVAILABILITY: The algorithm can be publicly accessed and used for the annotation of sequences through a web server at http://www.bork.embl.de/kat

SUMMARY: BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region. AVAILABILITY: The program is available upon request from the authors. A web server of BLAST2GENE is maintained at http://www.bork.embl.de/blast2gene

MOTIVATION: The analysis of protein-protein interactions allows for detailed exploration of the cellular machinery. The biochemical purification of protein complexes followed by identification of components by mass spectrometry is currently the method, which delivers the most reliable information--albeit that the data sets are still difficult to interpret. Consolidating individual experiments into protein complexes, especially for high-throughput screens, is complicated by many contaminants, the occurrence of proteins in otherwise dissimilar purifications due to functional re-use and technical limitations in the detection. A non-redundant collection of protein complexes from experimental data would be useful for biological interpretation, but manual assembly is tedious and often inconsistent. RESULTS: Here, we introduce a measure to define similarity within collections of purifications and generate a set of minimally redundant, comprehensive complexes using unsupervised clustering. AVAILABILITY: Programs and results are freely available from http://www.bork.embl-heidelberg.de/Docu/purclust/

Recent advances in proteomics and computational biology have lead to a flood of protein interaction data and resulting interaction networks (e.g. (Gavin et al., 2002)). Here I first analyse the status and quality of parts lists (genes and proteins), then comparatively assess large-scale protein interaction data (von Mering et al., 2002) and finally try to identify biological meaningful units (e.g. pathways, cellular processes) within interaction networks that are derived from the conservation of gene neighborhood (Snel et al., 2002). Possible extensions of gene neighborhood analysis to eukaryotes (von Mering and Bork, 2002) will be discussed.

SUMMARY: Network Analysis Interface for Linking HMMER results (NAIL) is a web-based tool for the analysis of results from a HMMER protein database-search. NAIL facilitates the selection of protein hits and the creation of an alignment, which can be used for a new sequence similarity search.

MOTIVATION: Computer-based selection of entries from sequence databases with respect to a related functional description, e.g. with respect to a common cellular localization or contributing to the same phenotypic function, is a difficult task. Automatic semantic analysis of annotations is not only hampered by incomplete functional assignments. A major problem is that annotations are written in a rich, non-formalized language and are meant for reading by a human expert. This person can extract from the text considerably more information than is immediately apparent due to his extended biological background knowledge and logical reasoning. APPROACH: A technique of automated annotation evaluation based on a combination of lexical analysis and the usage of biological rule libraries has been developed. The proposed algorithm generates new functional descriptors from the annotation of a given entry using the semantic units of the annotation as prepositions for implications executed in accordance with the rule library. RESULTS: The prototype of a software system, the Meta_A(nnotator) program, is described and the results of its application to sequence attribute assignment and sequence selection problems, such as cellular localization and sequence domain annotation of SWISS-PROT entries, are presented. The current software version assigns useful subcellular localization qualifiers to approximately 88% of all SWISS-PROT entries. As shown by demonstrative examples, the combination of sequence and annotation analysis is a powerful approach for the detection of mutual annotation/sequence inconsistencies. AVAILABILITY: Results for the cellular localization assignment can be viewed at the URL http://www.bork. embl-heidelberg.de/CELL_LOC/CELL_LOC.html.

MOTIVATION: We present a new concept that combines data storage and data analysis in genome research, based on an associative network memory. As an illustration, 115 000 conserved regions from over 73 000 published sequences (i.e. from the entire annotated part of the SWISSPROT sequence database) were identified and clustered by a self-organizing network. Similarity and kinship, as well as degree of distance between the conserved protein segments, are visualized as neighborhood relationship on a two-dimensional topographical map. RESULTS: Such a display overcomes the restrictions of linear list processing and allows local and global sequence relationships to be studied visually. Families are memorized as prototype vectors of conserved regions. On a massive parallel machine, clustering and updating of the database take only a few seconds; a rapid analysis of incoming data such as protein sequences or ESTs is carried out on present-day workstations. AVAILABILITY: Access to the database is available at http://www.bioinf.mdc-berlin.de/unter2.html++ + CONTACT: (hanke,lehmann,reich)@mdc-berlin.de; bork@embl-heidelberg.de

MOTIVATION: The underlying error rate for genomic sequencing sometimes results in the introduction of artificial frameshifts and in-frame stop codons into putative protein encoding genes. Severe errors are then introduced into the inferred transcripts through mis-translation or premature termination. RESULTS: We describe a system for screening segments of DNA for frameshift and in-frame stop errors in coding regions. The method is based on homology matching using blastx to compare all six reading frames of the query nucleotide sequence against selected protein sequence databases. Fragments of protein matching neighbouring regions of the query DNA are united and extended laterally to define candidate open reading frames, within which, frameshifts and stops are identified. Suitable targets include prokaryotic or other intron-free genomic sequence and complementary DNAs. As an example of its use, we report here two frameshifted ORFs that deviate from the original TIGR sequence annotations for the recently released Helicobacter pylori genome. AVAILABILITY: The tool is accessible via the URL http://www.sander.ebi.ac.uk/frame/. CONTACT: brown@ebi.ac.uk.

MOTIVATION: The untranslated regions (UTRs) of mRNA upstream (5'UTR) and downstream (3'UTR) of the open reading frame, as well as the mRNA precursor, carry important regulatory sequences. To reveal unidentified regulatory signals, we combine information from experiments with computational approaches. Depending on available knowledge, three different strategies are employed. RESULTS: Searching with a consensus template, new RNAs with regulatory RNA elements can be identified in genomic screens. By this approach, we identify new candidate regulatory motifs resembling iron-responsive elements in the 5'UTRs of HemA, FepB and FrdB mRNA from Escherichia coli. If an RNA element is not yet defined, it may be analyzed by combining results from SELEX (selective enrichment of ligands by exponential amplification) and a search of databases from RNA or genomic sequences. A cleavage stimulating factor (CstF) binding element 3 of the polyadenylation site in the mRNA precursor serves as a test example. Alternatively, the regulatory RNA element may be found by studying different RNA foldings and their correlation with simple experimental tests. We delineate a novel instability element in the 3'UTR of the estrogen receptor mRNA in this way. AVAILABILITY: Strategy, methods and programs are available on request from T.Dandekar. CONTACT: dandekar@embl-heidelberg.de

MOTIVATION: Numerous homologous sequences from diverse species can be retrieved from databases using programs such as BLAST. However, due to multigene families, evolutionary relationship often cannot be easily determined and proper functional assignment becomes difficult. Thus, discrimination between orthologues and paralogues within BLAST output lists of homologous sequences becomes more and more important. RESULT: We therefore developed a method that attempts to construct a reconciled tree from a gene tree of selected sequences and its corresponding phylogenetic tree of the species involved (species tree). An interface on the Web is developed to enable users to analyse the BLAST result. BLAST outputs are parsed and, for the selected sequences, multiple alignments are constructed either globally or for local regions. Bootstrapped trees are returned and compared with the expected species tree. In cases of discrepancies, gene duplications are assumed and a reconciled tree is computed. The reconciled tree shows probable orthologues and paralogues as predicted.