Multiplex Identification of Antigen-Specific T Cell Receptors Using a Combination of Immune Assays and Immune Receptor Sequencing.

Monitoring antigen-specific T cells is critical for the study of immune responses and development of biomarkers and immunotherapeutics. We developed a novel multiplex assay that combines conventional immune monitoring techniques and immune receptor repertoire sequencing to enable identification of T cells specific to large numbers of antigens simultaneously. We multiplexed 30 different antigens and identified 427 antigen-specific clonotypes from 5 individuals with frequencies as low as 1 per million T cells.

Genome and proteome annotation using automatically recognized concepts and functional networks.

Many tools have been developed for prediction of the function or disease association of genes and proteins, and this continues to be a highly active area of bioinformatics research. Typically, these methods predict which concepts should be annotated to genes or proteins, using terms from ontologies such as Gene Ontology (GO), largely overlooking other ontologies that are available. Here, we set out to broadly evaluate novel, automatically retrieved, gene-term annotations and identify those concepts of publicly available ontologies that can be predicted using a generalized tool for prediction of annotations.

STOP using just GO: a multi-ontology hypothesis generation tool for high throughput experimentation.

Background: Gene Ontology (GO) enrichment analysis remains one of the most common methods for hypothesis generation from high throughput datasets. However, we believe that researchers strive to test other hypotheses that fall outside of GO. Here, we developed and evaluated a tool for hypothesis generation from gene or protein lists using ontological concepts present in manually curated text that describes those genes and proteins.

A large-scale evaluation of computational protein function prediction.

Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is crucial that the accuracy of these methods be high.

Density parameter estimation for finding clusters of homologous proteins--tracing actinobacterial pathogenicity lifestyles.

Motivation: Homology detection is a long-standing challenge in computational biology. To tackle this problem, typically all-versus-all BLAST results are coupled with data partitioning approaches resulting in clusters of putative homologous proteins. One of the main problems, however, has been widely neglected: all clustering tools need a density parameter that adjusts the number and size of the clusters.

Genetic correction of Huntington's disease phenotypes in induced pluripotent stem cells.

Huntington's disease (HD) is caused by a CAG expansion in the huntingtin gene. Expansion of the polyglutamine tract in the huntingtin protein results in massive cell death in the striatum of HD patients. We report that human induced pluripotent stem cells (iPSCs) derived from HD patient fibroblasts can be corrected by the replacement of the expanded CAG repeat with a normal repeat using homologous recombination, and that the correction persists in iPSC differentiation into DARPP-32-positive neurons in vitro and in vivo.

DEFOG: discrete enrichment of functionally organized genes.

High-throughput biological experiments commonly result in a list of genes or proteins of interest. In order to understand the observed changes of the genes and to generate new hypotheses, one needs to understand the functions and roles of the genes and how those functions relate to the experimental conditions. Typically, statistical tests are performed in order to detect enriched Gene Ontology categories or pathways, i.

clusterMaker: a multi-algorithm clustering plugin for Cytoscape.

Background: In the post-genomic era, the rapid increase in high-throughput data calls for computational tools capable of integrating data of diverse types and facilitating recognition of biologically meaningful patterns within them. For example, protein-protein interaction data sets have been clustered to identify stable complexes, but scientists lack easily accessible tools to facilitate combined analyses of multiple data sets from different types of experiments. Here we present clusterMaker, a Cytoscape plugin that implements several clustering algorithms and provides network, dendrogram, and heat map views of the results.

Comprehensive cluster analysis with Transitivity Clustering.

Transitivity Clustering is a method for the partitioning of biological data into groups of similar objects, such as genes, for instance. It provides integrated access to various functions addressing each step of a typical cluster analysis. To facilitate this, Transitivity Clustering is accessible online and offers three user-friendly interfaces: a powerful stand-alone version, a web interface, and a collection of Cytoscape plug-ins.

Efficient online transcription factor binding site adjustment by integrating transitive graph projection with MoRAine 2.0.

Unlabelled: We investigated the problem of imprecisely determined prokaryotic transcription factor (TF) binding sites (TFBSs). We found that the identification and reinvestigation of questionable binding motifs may result in improved models of these motifs. Subsequent modelbased predictions of gene regulatory interactions may be performed with increased accuracy when the TFBSs annotation underlying these models has been re-adjusted.

Integrated analysis and reconstruction of microbial transcriptional gene regulatory networks using CoryneRegNet.

CoryneRegNet is the reference database and analysis platform for corynebacterial gene regulatory networks. It provides web-based access to integrated data on gene regulatory interactions of corynebacteria relevant to human medicine and biotechnology, Escherichia coli and Mycobacterium tuberculosis. To facilitate the analysis and reconstruction of the corresponding networks, CoryneRegNet provides user-friendly interfaces for bioinformatics analysis and network visualization tools.

MoRAine--a web server for fast computational transcription factor binding motif re-annotation.

Background: A precise experimental identification of transcription factor binding motifs (TFBMs), accurate to a single base pair, is time-consuming and diffcult. For several databases, TFBM annotations are extracted from the literature and stored 5' --> 3' relative to the target gene. Mixing the two possible orientations of a motif results in poor information content of subsequently computed position frequency matrices (PFMs) and sequence logos.

Exact and heuristic algorithms for weighted cluster editing.

Clustering objects according to given similarity or distance values is a ubiquitous problem in computational biology with diverse applications, e.g., in defining families of orthologous genes, or in the analysis of microarray experiments.

Large scale clustering of protein sequences with FORCE -A layout based heuristic for weighted cluster editing.

Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clustering approaches, following different strategies, have been published to attack this problem. Today, new sequencing technologies provide huge amounts of sequence data that has to be efficiently clustered with constant or increased accuracy, at increased speed.

CoryneRegNet 3.0--an interactive systems biology platform for the analysis of gene regulatory networks in corynebacteria and Escherichia coli.

CoryneRegNet is an ontology-based data warehouse for the reconstruction and visualization of transcriptional regulatory interactions in prokaryotes. To extend the biological content of CoryneRegNet, we added comprehensive data on transcriptional regulations in the model organism Escherichia coli K-12, originally deposited in the international reference database RegulonDB. The enhanced web interface of CoryneRegNet offers several types of search options.