Featured Websites

Patrocles

October 5, 2014 |

Polymorphic miRNA-mediated gene regulation in vertebrates ...

NPIDB: a database of nucleic acids-protein interactions.

October 5, 2014 |

The database NPIDB (Nucleic Acids-Protein Interaction DataBase) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from PDB (1834 complexes in July 2007). It is organized as a collection of files in PDB format and is equipped with a web-interface and a se...

A better block partition and ligation strategy for individual haplotyping.

October 5, 2014 |

Profile Comparer (PRC) is a stand-alone program for scoring and aligning profile hidden Markov models (HMMs) of protein families. PRC can read models produced by SAM and HMMER, two popular profile HMM packages, as well as PSI-BLAST checkpoint files. This application note provides a brief description...

ParaSAM: a parallelized version of the significance analysis of microarrays algorithm.

October 5, 2014 |

MOTIVATION: A large part of the maize B73 genome sequence is now available and emerging sequencing technologies will offer cheap and easy ways to sequence areas of interest from many other maize genotypes. One of the steps required to turn these sequences into valuable information is gene content pr...

InCroMAP: integrated analysis of cross-platform microarray and pathway data.

October 5, 2014 |

Comparative methods for RNA secondary structure prediction use evolutionary information from RNA alignments to increase prediction accuracy. The model is often described in terms of stochastic context-free grammars (SCFGs), which generate a probability distribution over secondary structures. It is, ...

Structure-based evaluation of in silico predictions of protein-protein interactions using Comparative Docking.

October 5, 2014 |

We have developed a web service that provides a comprehensive analysis of the susceptibility of cells to undergo apoptosis in response to an activation of the mitochondrial apoptotic pathway. Based on ordinary differential equations, (pre-determined) protein concentrations and release kinetics of mi...

MOBI: a web server to define and visualize structural mobility in NMR protein ensembles.

October 5, 2014 |

MOTIVATION: MOBI is a web server for the identification of structurally mobile regions in NMR protein ensembles. It provides a binary mobility definition that is analogous to the commonly used definition of intrinsic disorder in X-ray crystallographic structures. At least three different use cases c...

TIGR Gene Indices

October 5, 2014 |

Non-redundant, gene-oriented clusters ...

GraphClust: alignment-free structural clustering of local RNA secondary structures.

October 5, 2014 |

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions...

AAindex

October 5, 2014 |

Physicochemical and biological properties of amino acids ...


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>