Systems biology research is like solving a puzzle: the goal is to figure out how the various parts interact and work together. The interactome of an organism is then analogous to the puzzle’s key: it describes the network of all the protein–protein interactions (PPIs). As such, identifying all the PPIs for an organism is of great value. Despite the use of high-throughput techniques in discovering PPIs, however, the coverage of experimentally determined PPI data remains poor. Such low coverage is partly because the set of possible PPIs to be verified is so large that any exhaustive experimental verification will take a long time, even with high-throughput techniques.
Serves for the functional analysis of gene expression and genomic data. Babelomics offers the possibility to explore the effects of alteration in gene expression levels or changes in genes sequences within a functional context. It provides user-friendly access to a full range of methods that cover: (1) primary data analysis; (2) a variety of tests for different experimental designs; and (3) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context.
Aims to proteomics data analyses. Perseus extracts biologically meaningful information from processed raw files. It uses bioinformatic analyses from MaxQuant output and completes the proteomics analysis pipeline. It contains various statistical methods or illustrations (data transformation, normalization, imputation, and more). This tool gets five main interfaces: (1) data upload, (2) export, (3) processing, (4) analysis and (5) multimatrix handling.
Offers methods for structure prediction, design, and remodeling of proteins and nucleic acids. Rosetta provides a software suite for modeling macromolecular structures. This resource permits users to: (i) understand macromolecular interactions, (ii) design custom molecules, (iii) develop ways to search conformation and sequence space, and (iv) find energy functions for various biomolecular representations.
An analytical solution for biological researchers and incorporates an expansive knowledge base of molecular facts that enable researchers to connect independent research findings to gain new insights, to analyze and interpret the results of biological experiments, and to build biological models to develop new hypotheses and to communicate and publish complex biological concepts. Incorporating compelling interactive graphics, Pathway Studio helps researchers work more rapidly and with more confidence than performing manual research through articles. It further helps avoid repeating previously conducted research, and can produce more compelling research conclusions from experimental process.
A web interface to protein interaction data consolidated from 10 public databases: BIND, BioGRID, CORUM, DIP, IntAct, HPRD, MINT, MPact, MPPI and OPHID. iRefWeb enables users to examine aggregated interactions for a protein of interest, and presents various statistical summaries of the data across databases, such as the number of organism-specific interactions, proteins and cited publications.
Molecular interaction data exists in a number of repositories, each with its own data format, molecule identifier and information coverage. MiMI assists scientists searching through this profusion of molecular interaction data. The original release of MiMI gathered data from well-known protein interaction databases, and deep merged this information while keeping track of provenance.
Addresses some of the short comings of currently available methods for clustering gene expression data. HOPACH constructs a hierarchical tree whose final level is an ordered list of elements. It applies partitioning and collapsing steps to proceed. This tool lifts the binary split restriction to assist in detecting clusters. It can improve the final ordering produced, even when the algorithm is otherwise identical.