Consistency,comprehensiveness, and compatibility of pathway databases

Background  

It is necessary to analyze microarray experiments together with biological information to make better biological inferences. We investigate the adequacy of current biological databases to address this need.     

A traveling salesman approach for predicting protein functions

Background  

Protein-protein interaction information can be used to predict unknown protein functions and to help study biological pathways.     

Using mechanistic Bayesian networks to identify downstream targets of the Sonic Hedgehog pathway

Background  

The topology of a biological pathway provides clues as to how a pathway operates, but rationally using this topology information with observed gene expression data remains a challenge.     

Thesaurus-based disambiguation of gene symbols

Background  

Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene symbols is a major bottleneck.     

Integrated analysis of gene expression by association rules discovery

Background  

Microarray technology is generating huge amounts of data about the expression level of thousands of genes, or even whole genomes, across different experimental conditions. To extract biological knowledge, and to fully understand such datasets, it is essential to include external biological information about genes and gene products to the analysis of expression data. However, most of the current approaches to analyze microarray datasets are mainly focused on the analysis of experimental data, and external biological information is incorporated as a posterior process.     

Atlas – a data warehouse for integrative bioinformatics

Background  

We present a biological data warehouse called Atlas that locally stores and integrates biological sequences, molecular interactions, homology information, functional annotations of genes, and biological ontologies. The goal of the system is to provide data, as well as a software infrastructure for bioinformatics research and development.     

DNA microarray data and contextual analysis of correlation graphs

Background  

DNA microarrays are used to produce large sets of expression measurements from which specific biological information is sought. Their analysis requires efficient and reliable algorithms for dimensional reduction, classification and annotation.     

Encoding the states of interacting proteins to facilitate biological pathways reconstruction

Background  

In a systems biology perspective, protein-protein interactions (PPI) are encoded in machine-readable formats to avoid issues encountered in their retrieval for the reconstruction of comprehensive interaction maps and biological pathways. However, the information stored in electronic formats currently used doesn't allow a valid automatic reconstruction of biological pathways.     

KID - an algorithm for fast and efficient text mining used to automatically generate a database containing kinetic information of enzymes

Background  

The amount of available biological information is rapidly increasing and the focus of biological research has moved from single components to networks and even larger projects aiming at the analysis, modelling and simulation of biological networks as well as large scale comparison of cellular properties. It is therefore essential that biological knowledge is easily accessible. However, most information is contained in the written literature in an unstructured way, so that methods for the systematic extraction of knowledge directly from the primary literature have to be deployed.     

PathSys: integrating molecular interaction graphs for systems biology

Background  

The goal of information integration in systems biology is to combine information from a number of databases and data sets, which are obtained from both high and low throughput experiments, under one data management scheme such that the cumulative information provides greater biological insight than is possible with individual information sources considered separately.     

SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology

Background  

The biological information in genomic expression data can be understood, and computationally extracted, in the context of systems of interacting molecules. The automation of this information extraction requires high throughput management and analysis of genomic expression data, and integration of these data with other data types.     

OntoDas – a tool for facilitating the construction of complex queries to the Gene Ontology

Background  

Ontologies such as the Gene Ontology can enable the construction of complex queries over biological information in a conceptual way, however existing systems to do this are too technical. Within the biological domain there is an increasing need for software that facilitates the flexible retrieval of information. OntoDas aims to fulfil this need by allowing the definition of queries by selecting valid ontology terms.     

Tools enabling the elucidation of molecular pathways active in human disease: Application to Hepatitis C virus infection

Background  

The extraction of biological knowledge from genome-scale data sets requires its analysis in the context of additional biological information. The importance of integrating experimental data sets with molecular interaction networks has been recognized and applied to the study of model organisms, but its systematic application to the study of human disease has lagged behind due to the lack of tools for performing such integration.     

A-MADMAN: Annotation-based microarray data meta-analysis tool

Background  

Publicly available datasets of microarray gene expression signals represent an unprecedented opportunity for extracting genomic relevant information and validating biological hypotheses. However, the exploitation of this exceptionally rich mine of information is still hampered by the lack of appropriate computational tools, able to overcome the critical issues raised by meta-analysis.     

Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays

Background  

Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis.     

FunSpec: a web-based cluster interpreter for yeast

Background  

For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time.     

ProFAT: a web-based tool for the functional annotation of protein sequences

Background  

The functional annotation of proteins relies on published information concerning their close and remote homologues in sequence databases. Evidence for remote sequence similarity can be further strengthened by a similar biological background of the query sequence and identified database sequences. However, few tools exist so far, that provide a means to include functional information in sequence database searches.     

Moara: a Java library for extracting and normalizing gene and protein mentions

Background  

Gene/protein recognition and normalization are important preliminary steps for many biological text mining tasks, such as information retrieval, protein-protein interactions, and extraction of semantic information, among others. Despite dedication to these problems and effective solutions being reported, easily integrated tools to perform these tasks are not readily available.     

Critical evaluation of the JDO API for the persistence and portability requirements of complex biological databases

Background  

Complex biological database systems have become key computational tools used daily by scientists and researchers. Many of these systems must be capable of executing on multiple different hardware and software configurations and are also often made available to users via the Internet. We have used the Java Data Object (JDO) persistence technology to develop the database layer of such a system known as the SigPath information management system. SigPath is an example of a complex biological database that needs to store various types of information connected by many relationships.     

BFL: a node and edge betweenness based fast layout algorithm for large scale networks

Background  

Network visualization would serve as a useful first step for analysis. However, current graph layout algorithms for biological pathways are insensitive to biologically important information, e.g. subcellular localization, biological node and graph attributes, or/and not available for large scale networks, e.g. more than 10000 elements.