Gene Expression Data Analysis
Enrichr [Enrichr website]
PMID: 23586463 | PMCID: PMC3637064 | EndNote Citation
Genome-wide mRNA profiling provides a snapshot of the global state of cells under different conditions. However, mRNA levels do not provide direct understanding of upstream regulatory mechanisms. Here, we present a new approach called Expression2Kinases (X2K) to identify upstream regulators likely responsible for observed patterns in genome-wide gene expression. By integrating ChIP-seq/chip and position-weight-matrices (PWMs) data, protein-protein interactions, and kinase-substrate phosphorylation reactions, we can better identify regulatory mechanisms upstream of genome-wide differences in gene expression. We validated X2K by applying it to recover drug targets of FDA approved drugs from drug perturbations followed by mRNA expression profiling; to map the regulatory landscape of 44 stem cells and their differentiating progeny; to profile upstream regulatory mechanisms of 327 breast cancer tumors; and to detect pathways from profiled hepatic stellate cells and hippocampal neurons. The X2K approach can advance our understanding of cell signaling and unravel drugs mechanisms of action. The software and source code are freely available at: http://www.maayanlab.net/X2K.
PMID: 22080467 | EndNote Citation
GATE (Grid Analysis of Time-series Expression)
GATE is a computational software platform for integrated visualization and analysis of expression time-series. 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 | PMCID: PMC2796822 | EndNote Citation | Biositemaps (RDF)
Tech news feature on CNET: New database could speed up drug discovery
Article in Biomedical Computation Review: Animating molecular biology
Article in Nature Biotechnology: Systematic tracking of cell fate changes
Article about GATE on NIGMS website: Computational honeycombs drip with data
Blog post about GATE on Scientific American: Molecular movies: New software animates gene expression data
Gene-list Enrichment Analysis
ChEA (ChIP-X Enrichment Analysis) [ChEA website]
ChEA is a web-based system where users can input lists of mammalian gene symbols for which the program computes over-representation of transcription factor targets from the ChIP-X database. To build the ChIP-X database we collected interactions from high throughput ChIP experiments to construct a mammalian ChIP-X database.
PMID: 20709693 | | EndNote Citation
Genes2Networks [Genes2Networks website]
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 | PMCID: PMC2082048 |EndNote Citation | Biositemaps (RDF)
KEA (Kinase Enrichment Analysis) [KEA website]
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 computes 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 | PMCID: PMC2647829 | EndNote Citation | Biositemaps (RDF)
Lists2Networks (Integrated Analysis for Lists of Mammalian Genes) [Lists2Networks website]
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 | PMCID: PMC2843617 | EndNote Citation | Biositemaps (RDF)
Network2Canvas [Network2Canvas website]
PMID: 23749960 | | EndNote Citation
Genes2FANs [Genes2FANs website]
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 | PMCID: PMC3472228 | EndNote Citation
Sets2Networks [Sets2Networks website]
A 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 | PMCID: PMC344364 | EndNote Citation
Genes2WordCloud [Genes2WordCloud website]
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. It provides users with several different options and ideas for the sources that can be used to generate word-clouds. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice. Genes2WordCloud is a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies.
PMID: 21995939 | EndNote Citation
FNV (Flash-based Network Viewer) [FNV website]
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 | EndNote Citation | Biositemaps (RDF)
SNAVI (Signaling Network Analysis and Visualization) [SNAVI website]
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 | PMCID: PMC2637233 | EndNote Citation | Biositemaps (RDF)
PathwayGenerator [PathwayGenerator website]
PathwayGenerator web-interface 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 | PMCID: PMC3032439 | EndNote Citation | Biositemaps (RDF)
AVIS (AJAX Viewer for Signaling Networks) [AVIS website]
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 | PMCID: PMC2724864 | EndNote Citation | Biositemaps (RDF)
Sig2BioPAX [Sig2BioPAX website]
Sig2BioPAX is a 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 | PMCID: PMC3071313 | Biositemaps (RDF)
Excel2BiositemapsAndHTML [Excel2Biositemaps website]
Excel2Biositemaps is a tool that is used to convert an Excel file containing details about biomedical resources (tools, data, and software) into a Biositemaps .rdf file. A Biositemap file is a list of controlled metadata about resources. This file can be picked up and read by a number of search engines, the Biositemaps Search Tool or the Resource Discovery System, for example.