Featured Websites

Network-based comparison of temporal gene expression patterns.

October 5, 2014 |

MOTIVATION: Advances in the field of cheminformatics have been hindered by a lack of freely available tools. We have created Chembench, a publicly available cheminformatics portal for analyzing experimental chemical structure-activity data. Chembench provides a broad range of tools for data visualiz...

QOMA: quasi-optimal multiple alignment of protein sequences.

October 5, 2014 |

The R package mosclust (model order selection for clustering problems) implements algorithms based on the concept of stability for discovering significant structures in bio-molecular data. The software library provides stability indices obtained through different data perturbations methods (resampli...

Inherent limitations in protein-protein docking procedures.

October 5, 2014 |

MOTIVATION: Based on a gene classification into hierarchical categories (BINs), MapMan was originally developed to display Arabidopsis thaliana gene expression in a functional context. We have created a bioinformatics system to extend MapMan to any organism by using a new BIN structure based on the ...

Detection of stoichiometric inconsistencies in biomolecular models.

October 5, 2014 |

The accuracy of current signal peptide predictors is outstanding. The most successful predictors are based on neural networks and hidden Markov models, reaching a sensitivity of 99% and an accuracy of 95%. Here, we demonstrate that the popular BLASTP alignment tool can be tuned for signal peptide pr...

TIGR Comprehensive Microbial Resource

October 5, 2014 |

Completed microbial genomes ...

HaploPainter: a tool for drawing pedigrees with complex haplotypes.

October 5, 2014 |

SUMMARY: HaploPainter is a user-friendly pedigree-drawing application with special features for easy visualization of complex haplotype information. It has been developed to facilitate gene mapping in Mendelian diseases in terms of fast and reliable definition of the smallest critical interval harbo...

WEBnm@: a web application for normal mode analyses of proteins.

October 5, 2014 |

BACKGROUND: Normal mode analysis (NMA) has become the method of choice to investigate the slowest motions in macromolecular systems. NMA is especially useful for large biomolecular assemblies, such as transmembrane channels or virus capsids. NMA relies on the hypothesis that the vibrational normal m...

Curation of viral genomes: challenges, applications and the way forward.

October 5, 2014 |

Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins i...

Mapping PDB chains to UniProtKB entries.

October 5, 2014 |

MOTIVATION: UniProtKB/SwissProt is the main resource for detailed annotations of protein sequences. This database provides a jumping-off point to many other resources through the links it provides. Among others, these include other primary databases, secondary databases, the Gene Ontology and OMIM. ...

PiNGO: a Cytoscape plugin to find candidate genes in biological networks.

October 5, 2014 |

PiNGO is a tool to screen biological networks for candidate genes, i.e. genes predicted to be involved in a biological process of interest. The user can narrow the search to genes with particular known functions or exclude genes belonging to particular functional classes. PiNGO provides support for ...

Protein-protein binding affinity prediction on a diverse set of structures.

MOTIVATION: Accurate binding free energy functions for protein-protein interactions are imperative for a wide range of purposes. Their construction is predicated upon ascertaining the factors that influence binding and their relative importance. A recent benchmark of binding affinities has allowed, for the first time, the evaluation and construction of binding free energy models using a diverse set of complexes, and a systematic assessment of our ability to model the energetics of conformational changes. RESULTS: We construct a large set of molecular descriptors using commonly available tools, introducing the use of energetic factors associated with conformational changes and disorder to order transitions, as well as features calculated on structural ensembles. The descriptors are used to train and test a binding free energy model using a consensus of four machine learning algorithms, whose performance constitutes a significant improvement over the other state of the art empirical free energy functions tested. The internal workings of the learners show how the descriptors are used, illuminating the determinants of protein-protein binding. AVAILABILITY: The molecular descriptor set and descriptor values for all complexes are available in the supplementary. A web server for the learners and coordinates for the bound and unbound structures can be accessed from the website: http://bmm.cancerresearchuk.org/%7EAffinity CONTACT: paul.bates@cancer.org.uk.

Reconstructing transcription factor activities in hierarchical transcription network motifs.

MOTIVATION: A knowledge of the dynamics of transcription factors is fundamental to understand the transcriptional regulation mechanism. Nowadays an experimental measure of transcription factor activities in vivo represents a challenge. Several methods have been developed to infer these activities from easily measurable quantities such as mRNA expression of target genes. A limitation of these methods is represented by the fact that they rely on very simple single-layer structures, typically consisting of one or more transcription factors regulating a number of target genes. RESULTS: We present a novel statistical inference methodology to reverse engineer the dynamics of transcription factors in hierarchical network motifs such as feed-forward loops. The approach we present is based on a continuous time representation of the system where the high level master transcription factor is represented as a two state Markov jump process driving a system of differential equations. We solve the inference problem using an efficient variational approach and demonstrate our method on simulated data and two real datasets. The results on real data show that the predictions of our approach can capture biological behaviours in a more effective way than single-layer models of transcription, and can lead to novel biological insights. AVAILABILITY: http://homepages.inf.ed.ac.uk/gsanguin/software.html CONTACT: g.sanguinetti@ed.ac.uk.

survcomp: an R/Bioconductor package for performance assessment and comparison of survival models.

SUMMARY: The survcomp package provides functions to assess and statistically compare the performance of survival/risk prediction models. It implements state-of-the-art statistics to (i) measure the performance of risk prediction models, (ii) combine these statistical estimates from multiple datasets using a meta-analytical framework, and (iii) statistically compare the performance of competitive models. AVAILABILITY: The R/Bioconductor package survcomp is provided open source under the Artistic-2.0 License with a user manual containing installation, operating instructions and use case scenarios on real datasets. survcomp requires R version 2.13.0 or higher.URL: http://bioconductor.org/packages/release/bioc/html/survcomp.html CONTACT: Benjamin Haibe-Kains <bhaibeka@jimmy.harvard.edu>, Markus Schröder <mschroed@jimmy.harvard.edu>