Software & DatabasesBack to top
Center for Complex Biological Systems (UC Irvine)
GPU Codes for 3D Model of Epidermal Development
We provide CUDA code for Nvidia GPUs of a 3D model of epidermal development. The model includes GPU implementation of the subcellular element method for 3D spatial cells, an intracellular gene network for each cell represented by a set of ODEs, cell-cell neighbor communication through Notch signaling as part of each cell’s internal gene network, and cell behaviors of growth and division.
A Gene Network Inference Tool
We provide our Objective-C (Cocoa for Mac, GNUstep for Linux/Windows) optimization framework to learn linear gene regulatory networks from various types of gene expression data. The optimization incorporates network sparsity constraint through L1 regularization as well as incorporation of existing network information. The framework can handle wild type, perturbation, gene knockout and heterozygous knockdown gene expression data.
Fast Numerical Algorithms for Stiff Reaction-Diffusion Equations
We provide Matlab and C codes based on a novel and efficient algorithm for Reaction-Diffusion equations that model spatial dynamics of complex biological systems. The numerical method used in the code is designed for effective treatment of stiff reactions in spatial systems.
Accelerated Stochastic Simulation Algorithm for Reaction Networks
This is an exact method for stochastic simulation of chemical reaction networks (Exact R-Leap) to accelerate the Stochastic Simulation Algorithm (SSA).
Dynamical Grammar Simulator
Plenum is a simulation software written in Mathematica for dynamical grammar models. Dynamical grammars are an elegant language for representing complex processes that include stochastic events and continuous dynamics.
Scientific Inference Systems Tools
This is a collection of software and packages for modeling and image analysis on systems inferences.
The Sigmoid Project (http://www.sigmoid.org)
The SIGMOID project is intended to produce a database of cellular signaling pathways and models thereof, to marshal the major forms of data and knowledge required as input to cellular modeling software and also to organize the outputs.
Center for Genome Dynamics (The Jackson Laboratory)
Mouse Phylogeny Viewer is a custom genome browser designed by the Center for Genome Dynamics. It provides the user with reliable and detailed answers to questions on the haplotype diversity and phylogenetic origin of the genetic variation underlying any genomic region of most laboratory strains (both classical and wild-derived).
Genome Interval Overlap Calculator is a general purpose application for calculating the interval-by-interval overlap between two input files. One use of this application is to use the output from the MouseIBS tool to “filter out” regions of the genome that are identical between two strains. This could be applied to QTLs, gene lists etc.
TreeQA is a quantitative genome wide association mapping algorithm. TreeQA utilizes local perfect phylogenies constructed in genomic regions exhibiting no evidence of historical recombination. By efficient algorithm design and implementation, TreeQA can efficiently conduct quantitative genome-wide association analysis and is more effective than the previous methods.
CGDSNP – SNP Database is a high quality single nucleotide polymorphism (SNP) database produced by the Center for Genome Dynamics with more than 8 Million SNPs from 74 strains of laboratory mice, drawn from several sources.
Imputed Mouse SNP Resource includes full-genome genotype imputations for 88 classical laboratory mouse strains. The tools allow you to filter the full data set down to a particular set of strains and region of interest. You can view the distribution of imputation confidence for the selected strains averaged over your region of interest and then download the filtered data.
Mouse Map Converter is a simple web interface for converting mouse genome coordinates between MIT Markers, Base Pair Positions and Centimorgan Positions. The conversion process is based on the mouse map described in “A New Standard Genetic Map for the Laboratory Mouse” by Cox et al. 2009.
MouseDivGeno is a R package specifically designed to genotype the Mouse Diversity Genotyping Array, an Affymetrix mouse genotyping array similar to the human SNP 6.0. MouseDivGeno contains functions which allow you to perform genotyping, identify probe sets potentially harboring a new mutation (Variable INtensity Oligonucleotide or VINO, here we call it a vinotyping) and perform CNV analysis.
SNPtools is a R package that selects SNPs from a set of inbred strains. The software queries the SNP files and quickly returns SNPs for the requested strains in the region of interest. It then allows the user to plot these SNPs, intersect them with genes and classify them.Back to top
Center for Modular Biology (Harvard University)
Cancer Module Map data mining website
Web access to our comprehensive modular analysis of transcriptional responses in human cancer, including the full cancer expression compendium, detailed clinical annotations, and all the significant modules. Various searching, browsing and visualization capabilities are provided. Segal, E., Friedman, N., Koller, D. & Regev, A. A module map showing conditional activity of expression modules in cancer. Nature Genetics 36, 1090-1098 (2004). [ PDF ]
Cichlid ESTs, gene index, and genomics database
1) Astatotilapia burtoni ESTs: Genbank accession numbers CN468542 – CN472211 Genbank accession numbers DY625779 – DY632420
2) TIGR Gene Index for Astatotilapia burtoni (in collaboration with John Quackenbush’s group): A gene index for A. burtoni (release 1.0) Release 2.0 is scheduled for early June, 2006.
3) Cichlid EST and microarray database (beta version): Cichlid genomics site. A comprehensive database resource that connects all sequenced clones to data, including pertinent information on physical location, array coordinates, BLAST results, and functional annotation. Fungal Orthogroups Repository
We provide the orthogroup assignments for all predicted protein-coding genes across 13 Ascomycete fungal genomes. Ilan Wapinski, Avi Pfeffer, Nir Friedman and Regev, A. A Natural history and evolutionary principles of gene duplication in fungi. Nature 449, 54-61 (2007).
A comprehensive tool for visualization, integration and analysis of genomic data, from a modular perspective. We have recently introduced a new tool, Genomica (now under separate funding) a redesign of GeneXPress to accommodate additional modular analysis. To facilitate Genomica’s use by any genomics researcher, we developed an extensive online tutorial and basic analysis packages for several organisms. Further resources for analysis were developed as an online repository (GeneSets, below). Segal, E., Kaushal, A., Yelensky, R., Pham, T., Regev, A., Koller, D. & Friedman, N. GeneXPress: a visualization and statistical analysis tool for gene expression and sequence data. Proc. 12th Intl Conf. on Intelligent Systems for Molecular Biology (2004). [ PDF ]
Mutation mapping method
Software for using microarray data on DNA hybridization to detect single feature polymorphisms (SFP) and use them to map genetic traits in crosses between different strain backgrounds.
SERV: Sequence-based Estimation of Repeat Variability
An algorithm to predict the variability of tandem repeats developed by the Center for Modular Biology.
Center for Quantitative Biology (Princeton University)
bioPIXIE is a novel system for biological data integration and visualization. It allows you to discover interaction networks and pathways in which your gene(s) of interest participate.
Generic Gene Ontology (GO) Term Finder
This generic (“multi-organism”) GO Term Finder web tool finds significant GO terms shared among a list of genes from your organism of choice, helping you discover what these genes may have in common. The implementation of this Generic GO Term Finder depends on the GO-TermFinder software written by Gavin Sherlock and Shuai Weng at Stanford University, made publicly available through the GMOD project.
Generic Gene Ontology (GO) Term Mapper
This generic (“multi-organism”) GO Term Mapper web tool maps the granular GO annotations for genes in a list to a set of GO slim terms, allowing you to bin your genes into broad categories. The implementation of this Generic GO Term Mapper uses map2slim.pl script written by Chris Mungall at Berkeley Drosophila Genome Project, and some of the modules included in the GO-TermFinder distribution written by Gavin Sherlock and Shuai Weng at Stanford University, made publicly available through the GMOD project.
MAVEN : an open source, cross platform metabolomics data analyzer
The aim of this software packages is to reduce complexity of metabolomics analysis by developing a highly intuitive interface for exploring and validating metabolomics data. The program features multi-file chromatographic aligner, peak-feature detector, isotope and adduct calculator, formula predictor, pathway visualizer, and isotopic flux animator. Data from both triple quadropole and full spectrum instruments is supported.
Nearest Neighbor Networks (NNN)
Nearest Neighbor Networks (NNN) is a graph-based algorithm used to cluster genes with similar microarray expression profiles. The NNN clustering method is an alternative to classical techniques such as hierarchical and K-means clustering. NNN generates clusters of functionally related genes with high precision, and the clusters generally represent a broader selection of biological processes than those produced by other methods; NNN performs best on data sets with many conditions and on datasets that are modular (i.e. contain several grouped subsets of conditions). The NNN algorithm is described in Huttenhower et al. 2007 and was developed in the Troyanskaya and Coller labs. The web tool was implemented by Juan Alvarez in the Bioinformatics group at Princeton [ download ]
SiteSifter finds highly conserved DNA motifs embedded within coding regions. Each instance of a motif is scored based on the chance that its constituent codons are conserved over and above that required for amino acid conservation.
Provides an analysis of yeast genes and their growth rate correlations.
P-POD : Princeton Protein Orthology Database
P-POD displays families of predicted orthologs from P. falciparum, H. sapiens, D. melanogaster, M. musculus, A. thaliana, C. elegans, D. rerio, and S. cerevisiae with an emphasis on providing information about disease-related genes and experimental confirmation of orthology from the literature.
Princeton University Microarray Database (PUMAdb)
The Princeton University MicroArray database (PUMAdb) stores raw and normalized data from microarray experiments, as well as their corresponding image files. In addition, PUMAdb provides interfaces for data retrieval, analysis and visualization. Princeton researchers and their collaborators should register for a database account [ download ] [ publications ]
Sleipnir Library for Computational Functional Genomics
Sleipnir is a C++ library enabling efficient analysis, integration, mining, and machine learning over genomic data. This includes a particular focus on microarrays, since they make up the bulk of available data for many organisms, but Sleipnir can also integrate a wide variety of other data types, from pairwise physical interactions to sequence similarity or shared transcription factor binding sites.
SPELL : Serial Pattern of Expression Levels Locator
SPELL (Serial Pattern of Expression Levels Locator) is a query-driven search engine for large gene expression microarray compendia. Given a small set of query genes, SPELL identifies which datasets are most informative for these genes, then within those datasets additional genes are identified with expression profiles most similar to the query set.
Virus Infection Project
The Virus Infection Project (VIP) is a web tool that provides a way to look at information about transcripts during CMV infections.
Yeast Functional Genomics Database (YFGdb)
The goal of YFGdb is to collect and freely disseminate all available yeast functional genomics data, along with requisite analysis tools, to the yeast community and the biomedical research community at large. YFGdb contains data sets from microarray as well as many other genomics/proteomics studies including large-scale interaction and phenotype experiments. YFGdb has been implemented using the Generic Model Organism Database Construction Set as part of the GMOD project.
Multiplexed Shotgun Genotyping (MSG)
Genotyping approach based on multiplexed shotgun sequencing that can identify recombination breakpoints in a large number of individuals simultaneously at a resolution sufficient for most mapping purposes, such as quantitative trait locus (QTL) mapping and mapping of induced mutations.
COALESCE uses large collections of genomic data and Bayesian integration to predict coregulated gene modules, the conditions of regulation, and the consensus binding motifs for regulation. It uses a synthesis of gene expression biclustering, motif prediction, and data integration (including expression, sequence, nucleosome positioning, and evolutionary conservation). It is available as part of the Sleipnir library.
PVIEW is an open source software tool for the visualization and analysis of high resolution quantitative proteomics and metabolomics LC-MS and LC-MS/MS data. PVIEW enables quantification of complex mixtures of proteins and metabolites.
Center for Systems and Synthetic Biology (UC San Francisco)
Biomedical research often focuses on altering the functions of selected proteins. These changes can unexpectedly perturb signaling pathways and non-specifically affect several cellular processes. PathwayLinker can assist experimental work by linking the queried proteins to signaling pathways through protein-protein and/or genetic interactions. PathwayLinker identifies and visualizes the first neighbor interactor network of the queried proteins, analyzes the signaling pathway memberships of the proteins in this subnet, and provides links to further online resources.
Recent advances in mass spectrometry have permitted the identification of thousands of posttranslational modifications (PTMs) including phosphorylation and ubiquitylation. But which modifications are actually biologically meaningful? In work published in Cell, Center investigators Nevan Krogan, Al Burlingame, Wendell Lim and colleagues developed a method of prioritizing PTMs, leading to predictors of functional relevance, and identification of regulatory hot spots. See PTMfunc for the database of PTM functional predictions.
CRNSimulator Mathematica Package: Many mathematical models in biology are described by ordinary differential equations, often derived from mass-action or Michaelis-Menten chemical kinetics. This is a Mathematica package for the syntactic manipulation of chemical reaction networks as Mathematica expressions, and for the simulation of such systems. It is particularly well-suited for engineered chemical systems, in which chemical reaction networks can be used as a kind of “programming language”.Back to top
San Diego Center for Systems Biology (UC San Diego)
Cytoscape is an open source software platform for visualizing molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data. Although Cytoscape was originally designed for biological research, now it is a general platform for complex network analysis and visualization. Cytoscape core distribution provides a basic set of features for data integration, analysis, and visualization. Additional features are available as Apps (formerly called Plugins). Apps are available for network and molecular profiling analyses, new layouts, additional file format support, scripting, and connection with databases. They may be developed by anyone using the Cytoscape open API based on Java™ technology and App community development is encouraged. Most of the Apps are freely available from Cytoscape App Store.
NeXO is a gene ontology inferred directly from large-scale molecular networks. A gene ontology provides structured knowledge about the cellular components, processes, and functions encoded by genes. While most ontologies – including the highly successful Gene Ontology Database (GO) – are constructed through manual expert curation, NeXO is a data-driven gene ontology inferred directly from ‘omics data. NeXO (The Network Extracted Ontology) uses a principled computational approach which integrates evidence from hundreds of thousands of individual gene and protein interactions to construct a complete hierarchy of cellular components and processes. This data-derived ontology aligns with known biological machinery in the GO Database and also uncovers many new structures.
HOMER (Hypergeometric Optimization of Motif EnRichment) is a suite of tools for Motif Discovery and next-gen sequencing analysis. It is a collection of command line programs for unix-style operating systems written in Perl and C++. HOMER was primarily written as a de novo motif discovery algorithm and is well suited for finding 8-20 bp motifs in large scale genomics data. HOMER contains many useful tools for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets.
Pathway alignment and query against protein interaction databases to identify conserved protein interaction networks between species. PathBLAST searches the protein-protein interaction network of the target organism to extract all protein interaction pathways that align with a pathway query.
Molecular interaction models provide us with a framework for integrating the large-scale data that we are now able to collect at multiple levels of biological information – genes, RNAs, proteins, and small molecules. Cell Circuit Search is a web-based interface for searching for genes that appear in our library of network models.
Center for Systems Biology (Institute for Systems Biology)
||Database and software integration framework – The Gaggle is a framework for exchanging data between independently developed software tools and databases to enable interactive exploration of systems biology data.||PMID:
||Information resource – Atlas for human, mouse; yeast peptides from large set of tandem mass spectrometry data. Results processed through Trans-Proteomic Pipeline||PMID:
||Data analysis software – a suite of software tools for the analysis of tandem mass spectrometry data sets. The tools encompass most of the steps in a proteomic data analysis workflow in a single, integrated software system. Specifically, the TPP supports all steps from spectrometer output file conversion to protein-level statistical validation, including quantification by stable isotope ratios.||PMID:
||Data analysis software – A peptide atlas for 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636,000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments.||PMID:
|Data analysis – An open source bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data.||PMID:
||Data management – An adaptable data management system designed to support the mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, and flow cytometry).||PMID:
||Data analysis – Designed to perform clustering analysis for data on the simplex space. Simcluster is a stand-alone command-line C package and user-friendly on-line tool.||PMID:
|Data analysis – An open source analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques, and (ii) probabilistic gene annotation.||PMID:
||Data analysis – A flexible, probabilistic framework to predict transcription factor binding from multiple data sources.||PMID:
Duke Center for Systems Biology
The CellTracer software for automated dynamic image analysis in single cell fluorescent microscopy studies.
Gene circuit simulation software
The Dynetica software for graphical construction of kinetic models and automatic generation of the implied differential equations, time course simulations using deteriministic or stochastic algorithms, and sensitivity analyses.
Statistical analysis software relevant for systems biological applications
The BFRM software for Bayesian Factor Regression Models — modelling and analysis of sparse latent factor models use in applications in pathway analysis and predictive modelling with large-scale gene expression data sets, with links to studies in gene expression analysis.
The GGM software for Bayesian analysis and search of graphical/network structures in the framework of Gaussian graphical models, with links to applications in gene expression studies.
The PRIORITY software package for de novo motif discovery based on Bayesian classifiers for identification of transcription factor binding sites.
General software and visualisation tools that may be of interest for systems biological application
The GraphExplore software for dynamically displaying, exploring and modifying large graphs and networks, with a range of visualisation and interactive analysis facilities
General statistical model search and analysis software applications
Additional Bayesian analysis software from Alex Hartemink’s group, including software for sparse multinomial ligistic regression model search, and for Bayesian network modelling
Additional Bayesian analysis software from Mike West’s group, including shotgun stochastic search (SSS) for linear and nonlinear regression models with many variables, time series analysis with flexible dynamic models, classification and prediction tree modelling, and others
Center for Applied Genomics & Technology software site.Back to top
New Mexico Center for Spatiotemporal Modeling of Cell Signaling
Image Analysis Tools
Led by S. Steinberg, the UNM image analysis team has developed sophisticated image processing and spatial statistics applications to acquire quantitative information from electron microscopy images, providing rich data sets for spatial stochastic models.
A complementary team led by K. Lidke is generating novel algorithms and software for the analysis of single particle tracking data generated by confocal, TIRF and hyperspectral microscopy.
Next, download the ParticlePicker plugin and the CoLocalization plugin. Copy these two files to the plugins directory of ImageJ (preferably, create separate folders under plugins to hold each file). Start ImageJ. Click “Plugins Compile and Run Plugin” to compile these two programs. (Note: since there is no image present, the Run part will produce errors which can safely be ignored.) Restarting ImageJ, you should see “ParticlePicker” and “Colocalization” in the Plugins menu. Further instructions on installation and usage of these plugins can be found in (ParticlePicker) [txt] AND [doc] [pdf] and (Colocalization) [doc] [pdf], respectively.
Also available is a program for cluster size analysis, a standalone application written in Visual Basic to draw a diagram of clustering and co-clustering using results from the ImageJ plugins.
cellspan, a GUI frontend for the R statistics package, computes Hopkins and Ripley (including bivariate Ripley) statistics for 5 and 10 nm particle positions. Full details and downloads can be found by following the link. Sample files for testing are positions_5.txt, positions_10.txt and croparea.txt.
Viewing MATLAB movies of particles
Download DIPimage, a MATLAB toolbox for scientific image processing and analysis. Next, create an initialization file like dip.m, which specifies where DIPimage is installed. If MATLAB is started in the directory where this file residues, typing “dip” will initialize DIPimage. Load an image file: “load(‘080220-1a’)”. If the image is contained in the variable “sequence”, “dipshow(sequence)” will display it, however, it is usually necessary to first execute Mappings -› Linear stretch to make the image visible. “dipimage” will bring up a variety of windows for further analyses.
STMC modelers are developing mathematical models of complex biological systems that play a role in cellular signaling. These models are being used to learn about specific systems, particularly signal transduction systems important in the immune system and cancer.
BioNetGen, developed by the LANL team as a general-purpose tool for computer-aided generation of rule-based deterministic or stochastic models of chemical reaction systems, is an example.Back to top
Systems Biology Center New York (SBCNY)
Gene Expression Data Analysis Tools
[PMID: 23586463] [Contact: Avi Ma’ayan]
Expression2Kinases (X2K) is new software developed by the Information Management Unit of SBCNY to identify upstream pathways likely responsible for observed changes in genome-wide gene expression. The software uses ChIP-seq/chip and position-weight-matrices (PWMs) data to identify enriched transcription factors upstream of differentially expressed genes; then protein-protein interactions to build subnetworks centered on the identified transcription factors; and then kinase-substrate phosphorylation reaction databases to infer upstream kinases regulating the proteins within the subnetwork. The software and source code are freely available at: http://www.maayanlab.net/X2K.
[PMID: 22080467] [Contact: Avi Ma’ayan]
GATE (Grid Analysis of Time-series Expression)
GATE is a computational software platform for integrated visualization and analysis of expression time-series data. Given a high-dimensional time-series dataset, GATE employs a clustering algorithm which creates movies of expression dynamics by assigning individual genes/proteins to hexagons on a hexagonal array and dynamically coloring each hexagon according to the expression level of the molecular species to which it is associated. Additionally, in order to infer potential regulatory control mechanisms from patterns of time-series correlations, GATE allows interactive interrogation of the movies with a wide variety of background knowledge datasets.
[PMID: 19892805] [Contact: Avi Ma’ayan]
Gene-list Enrichment Analysis Tools
ChEA (ChIP-X Enrichment Analysis)
The ChEA database contains manually extracted datasets of transcription-factor/target-gene interactions from over 100 experiments such as ChIP-chip, ChIP-seq, ChIP-PET applied to mammalian cells. We use the database to analyze mRNA expression data where we perform gene-list enrichment analysis as the prior biological knowledge gene-list library. The system is delivered as web-based interactive software. With this software users can input lists of mammalian genes for which the program computes over-representation of transcription factor targets from the ChEA database.
[PMID: 20709693] [Contact: Avi Ma’ayan]
Genes2Networks is a tool that can be used to place lists of mammalian genes in the context of a background mammalian signalome and interactome networks. The input to the program is a list of human Entrez Gene gene symbols and background networks in SIG format, while the output includes: (a) all identified interactions for the genes/proteins, (b) a subnetwork connecting the genes/proteins using intermediate components that are used to connect the genes, (c) ranking of the specificity of intermediate components to interact with the list of genes/proteins, and (d) a clustering analysis of the genes/proteins from the seed list based on their distance from one another in network space.
[PMID: 17916244] [Contact: Avi Ma’ayan]
KEA (Kinase Enrichment Analysis)
KEA is a web-based tool with an underlying database providing users with the ability to link lists of mammalian proteins/genes with the kinases that phosphorylate them. The system draws from several available kinase-substrate databases to compute kinase enrichment probability based on the distribution of kinase-substrate proportions in the background kinase-substrate database compared with kinases found to be associated with an input list of genes/proteins.
[PMID: 19176546] [Contact: Avi Ma’ayan]
Lists2Networks is a web-based system that will allow users to upload and analyze lists of mammalian gene-sets in a client-server-based software application. Within their workspace users can examine the overlap among the lists they upload, manipulate lists with different set operations, expand lists using existing mammalian networks of protein-protein, co-expression correlations, or background knowledge annotation correlations, and apply simple gene-set enrichment analyses on many gene lists at once against a plethora of background datasets.
[PMID: 20152038] [Contact: Avi Ma’ayan]
Network Analysis/Visualization Tools
Genes2FANs (G2F) is a web based tool and a database that utilizes 14 carefully constructed FANs and a large-scale protein-protein interaction (PPI) network to build subnetworks that connect input lists of human and mouse genes. The FANs are created from mammalian gene set libraries where mouse genes are converted to their human orthologs. The tool takes as input a list of human or mouse Entrez gene symbols to produce a subnetwork and a ranked list of intermediate genes that are used to connect the query input list. In addition, users can enter any PubMed search term and then the system automatically converts the returned results to gene lists using GeneRIF. This gene list is then used as input to generate a subnetwork from the user’s PubMed query.
[PMID: 22748121] [Contact: Avi Ma’ayan]
Sets2Networks (S2N) is general method for network inference from repeated observations of sets of related entities. Given experimental observations of sets of related entities, S2N infers the underlying network of binary interactions between these entities by generating an ensemble of networks consistent with the data; the frequency of occurrence of a given interaction throughout this ensemble is interpreted as the probability that the interaction is present in the underlying real network.
[PMID: 22824380] [Contact: Avi Ma’ayan]
Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds.
[PMID: 21995939] [Contact: Avi Ma’ayan]
FNV (Flash-based Network and Pathway Viewer)
FNV is written in Adobe ActionScript 3.0, the viewer accepts simple Extensible Markup Language (XML) formatted input files to display pathways in vector graphics on any web-page providing flexible layout options, interactivity with the user through tool tips, hyperlinks, and the ability to rearrange nodes on the screen. FNV was utilized as a component in several web-based systems, namely Genes2Networks, Lists2Networks, KEA, ChEA and PathwayGenerator. In addition, FNV can be used to embed pathways inside PDF files for the communication of pathways in soft publication materials.
[PMID: 21349871] [Contact: Avi Ma’ayan]
SNAVI (Signaling Network Analysis and Visualization)
SNAVI is Windows-based desktop application that implements standard network analysis methods to compute the clustering, connectivity distribution, and detection of network motifs, as well as provides means to visualize networks and network motifs. SNAVI is capable of generating linked web pages from network datasets loaded in text format. SNAVI can also create networks from lists of gene or protein names. SNAVI is a useful tool for analyzing, visualizing and sharing cell signaling data. SNAVI is open source free software.
[PMID: 19154595] [Contact: Avi Ma’ayan]
PathwayGenerator was created using the mammalian neuronal cell signaling network extracted from literature. A paper describing the topology of this network was published in Science in 2005. The network contains mostly directed and signed links (i.e. activation/inhibition with source and target nodes specified). Using Dijkstra’s shortest path algorithm, we searched for pathways starting from ligand-receptor interactions to reach effector proteins in a limited number of steps. The search was directed such that the flow must follow the orientation of the arrows. In total, approximately 5,000 pathways were created and can be visualized here. An implementation of the algorithm is provided with the SNAVI source code.
[PMID: 16099987] [Contact: Avi Ma’ayan]
AVIS (AJAX Viewer for Signaling Networks)
AVIS is a visualization tool for viewing and sharing intracellular signaling, gene regulation and protein interaction networks. AVIS is implemented as an AJAX enabled syndicated Google gadget. It allows any webpage to render an image from a text file representation of signaling, gene regulatory or protein interaction networks.
[PMID: 17855420] [Contact: Avi Ma’ayan]
Comand-line Java program that can be used to convert structured text files describing molecular interactions into the BioPAX Level 3 standard format.
[PMID: 21418653] [Contact: Avi Ma’ayan]
Compartmental Modeling Environment
MOOSE (Multiscale Object-oriented Simulation Environment)
MOOSE is designed to handle large complex simulations especially in biology. MOOSE spans the range from single molecules to subcellular networks, from single cells to neuronal networks, and to still larger systems. It is backwards-compatible with GENESIS, and forward compatible with Python and XML-based model definition standards like SBML and MorphML.
[PMID: 19129924] [Contact: Upinder Bhalla]
ESCAPE (Embryonic Stem Cells Atlas of Pluripotency Evidence)
ESCAPE is a mammalian embryonic stem cell specific database (Embryonic Stem Cell Atlas from Pluripotency Evidence). The database was created by collecting and integrating data reporting results from various published studies that profiled human and mouse ESCs including: protein-DNA binding interactions extracted from ChIP-seq/chip experiments, gene regulatory interactions from loss/gain-of-function studies followed by genome-wide mRNA expression profiling, protein interactions from immunoprecipitation followed by mass-spectrometry proteomics, a list of potential pluripotency regulators from RNA interference screens, ESC-specific proteins and phosphoproteins with specified phosphosites from proteomics and phosphoproteomics studies, time-course genome-wide mRNA microarray datasets from differentiating mouse ESCs, and histone modification status from genome-wide studies.
[Contact: Avi Ma’ayan]
iScMiD (Integrated Stem-Cell Molecular Interactions Database)
iScMiD is an initial database for disseminating and displaying gene regulatory networks in stem cells. It currently contains interactions from 12 recent publications of profiling stem-cell related transcription factors using various high throughput ChIP profiling methods. The resultant integrated network has 50,250 entries. The file contains four columns: transcription factor (TF), target gene, PubMed ID (pmid), and organism (mouse/human). Please be aware that this network is likely to contain many false-positives and should be used for hypothesis generation only.
[PMID: 19738627] [Contact: Avi Ma’ayan]
Presynaptome: Network of Protein-protein Interactions within the Synapse
Created to visualize and share, with the neuroscience and molecular biology research communities, information about proteins and interactions identified to be present in presynaptic nerve terminals of mammalian neurons. The web-site features a network of protein-protein interactions manually extracted from neuroscience research literature. The interactions in this network are identified to be exclusively from presynaptic nerve terminals of mammalian neurons.
[PMID: 19738627] [Contacts: Avi Ma’ayan and Lakshmi A. Devi]
DOQCS (Database of Quantitative Cellular Signaling)
DOQCS is a repository of models of signaling pathways. It includes reaction schemes, concentrations, rate constants, as well as annotations on the models. The database provides a range of search, navigation, and comparison functions.
[PMID: 12584128] [Contact: Upinder Bhalla]
Virtual Physiological Rat (University of Michigan)Back to top
Based on the network stoichiometry and sign constraints imposed on the boundary fluxes, this Matlab-based package is used to predict thermodynamically feasible reaction directions.Back to top
BELUGA is a MATLAB optimization package implementing a genetic algorithm based on PIKAIA. BELUGA finds a constrained local minimum x of an objective function given an initial population of candidate solutions.
The Biochemical Simulation Environment (BISEN) software package is a suite of tools for generating equations and associated computer programs for simulating biochemical systems. BISEN is described in a recent publication. The BISEN page provides links to a user manual with several tutorial examples of increasing complexity that demonstrate its current capabilities, and a download page.
A toolbox for causally cohesive genotype-phenotype studies.
Database of Thermodynamic Biochemical reactions
This web based bio-thermodynamic database can be used to obtain formation properties and dissociation constants (provided as pK’s) for reference species associated with biochemical reactants at specified temperature and ionic strength and to obtain reaction properties (including free energies and enthalpies) for associated reactions.
JSim is a Java-based simulation system for building quantitative numeric models and analyzing them with respect to experimental reference data. JSim’s primary focus is in physiology and biomedicine, however its computational engine is quite general and applicable to a wide range of scientific domains. JSim models may intermix ODEs, PDEs, implicit equations, integrals, summations, discrete events and procedural code as appropriate. JSim’s model compiler can automatically insert conversion factors for compatible physical units as well as detect and reject unit unbalanced equations. JSim also imports and exports model archive formats SBML and CellML.
This stand-alone package is used for computer-assisted derivation of rate equations for enzymes and transporters. It is based on the schematic methods of King and Altman and uses linear graph theory for generating valid King-Altman directed graphs. The package includes a graphical interface and can output derived rate equations in either MathML or MATLAB format.
Microvascular Mass Transport
A Matlab-based suite of tools for building models of microvascular transport and exchange from 3D structural information.
An experimental software tool for annotating biosimulation models with rich semantics and composing models in a modular, automated fashion.
A MATLAB tool for the specification, construction, and exact reduction of state transition system models of biochemical processes.