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http://medblast.sibsnet.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. An algorithm that finds articles most relevant to a genetic sequence. In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here, a new literature-mining tool MedBlast is developed, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided. The genome sequencing projects generate such a large amount of data every day that many molecular biologists often encounter some sequences that they know nothing about. Literature is usually the principal resource of such information. It is relatively easy to mine the articles cited by the sequence annotation; however, it is a difficult task to retrieve those relevant articles without direct citation relationship. The related articles are those described in the given sequence (gene/protein), or its redundant sequences, or the close homologs in various species. They can be divided into two classes: direct references, which include those either cited by the sequence annotation or citing the sequence in its text; indirect references, those which contain gene symbols of the given sequence. A few additional issues make the task even more complicated: (1) symbols may have aliases; and (2) one sequence may have a couple of relatives that we want to take into account too, which include redundant (e.g. protein and gene sequences) and close homologs. Here the issues are addressed by the development of the software MedBlast, which can retrieve the related articles of the given sequence automatically. MedBlast uses BLAST to extend homology relationships, precompiled species-specific thesauruses, a useful semantics technique in natural language processing (NLP), to extend alias relationship, and EUtilities toolset to search and retrieve corresponding articles of each sequence from PubMed. MedBlast take a sequence in FASTA format as input. The program first uses BLAST to search the GenBank nucleic acid and protein non-redundant (nr) databases, to extend to those homologous and corresponding nucleic acid and protein sequences. Users can input the BLAST results directly, but it is recommended to input the result of both protein and nucleic acid nr databases. The hits with low e-values are chosen as the relatives because the low similarity hits often do not contain specific information. Very long sequences, e.g. 100k, which are usually genomic sequences, are discarded too, for they do not contain specific direct references. User can adjust these parameters to meet their own needs.

Proper citation: MedBlast (RRID:SCR_008202) Copy   

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http://www.koki.hu/main.php?folderID=903

The aim of this laboratory is to understand how information is encoded in specific spatiotemporal activity patterns and structural configurations at the circuit, cellular, and molecular levels in the hippocampus, thereby enabling the process of memory. A major task is to find the neuronal codes of internal representations of memory items and the mapping rules between the levels of gene expression/proteins synthesis and the level of cognitive processing. Novel combinations of approaches, including multiple single-cell recording technology, patch-clamp electrophysiology, neuroanatomy/neurochemistry at the cellular and subcellular levels, and computational models are employed to test specific hypotheses about that mapping process (such as local circuit anatomy and activity-dependent short-term and long-term synaptic plasticity). Collaborations within the Institute allows the group to also incorporate gene targeting methods and behavioral learning/memory tests in their methodological repertoire. The laboratory has been focusing on the normal and pathological (epileptic, ischemic) activity of cortical networks, with particular attention to the generation of behaviour-dependent population discharge patterns (theta and gamma oscillations, hippocampal sharp waves). Anatomical, in vitro and in vivo electrophysiological, pharmacological and molecular techniques and modeling are combined to elucidate the functional roles of inhibitory cell types in the control of population synchrony and synaptic plasticity in the hippocampus, their local and subcortical modulation via selective afferent pathways (GABAergic and cholinergic septal, as well as serotonergic raphe input) and pre- or postsynaptic receptors. An expanding new direction of research is related to the role of endocannabinoid signaling in the activity-dependent modulation of GABAergic and glutamatergic transmission, and its involvement in anxiety-like behavior.

Proper citation: Institute of Experimental Medicine of the Hungarian Academy of Sciences: Laboratory of Cerebral Cortext Reserach (RRID:SCR_008041) Copy   

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http://www.mf.uni-lj.si/bitola/

An interactive literature-based biomedical discovery support system. The goal of this system is to discover new, potentially meaningful relations between a given starting concept of interest and other concepts, by mining the bibliographic database MEDLINE. To make the system more suitable for disease candidate-gene discovery and to decrease the number of candidate relations, we integrated background knowledge about the chromosomal location of the starting disease as well as the chromosomal location of the candidate genes from resources such as Entrez Gene, HUGO and OMIM. The BITOLA system can also be used as an alternative way of searching the Medline database. The system is available in two versions: closed discovery and open discovery. Closed discovery allows the input of two concepts (Example 1: a disorder and a gene. Example 2: a drug and a side effect) and generates potential explanations of the relationship between two entities. It does this by searching published literature to finds intermediate links. Open discovery allows the input of a single concept, then categories for first-order relatives of that concept, then categories for relatives of those first order concepts. Thus it can link from a disease to related drugs, then to genes related to those drugs and then test if those genes have been mentioned/tested in association with the disease. If the answer is no, then the gene is potentially related yet untested in the literature. Thus the open discovery tool is a nominator of new genes, drugs or neuroscience correlates to be investigated with diseases, disorders, physiological responses or any other phenotype.

Proper citation: BITOLA: Biomedical Discovery Support System (RRID:SCR_008175) Copy   

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http://www.affymetrix.com/support/developer/powertools/apt_archive.affx

Affymetrix Power Tools (APT) are a set of cross-platform command line programs that implement algorithms for analyzing and working with Affymetrix GeneChip arrays. APT programs are intended for power users who prefer programs that can be utilized in scripting environments and are sophisticated enough to handle the complexity of extra features and functionality. APT provides platform for developing and deploying new algorithms without waiting for the GUI implementations. This resource is supported by Affymetrix, Inc.

Proper citation: Affymetrix Power Tools (RRID:SCR_008401) Copy   

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http://mousemutant.jax.org/index.html

Producer and supplier of a collection of mice bearing spontaneous mutations. These mice contribute to a better understanding of the genetic bases of neurological, neuromuscular, sensory, metabolic, skeletal/craniofacial and developmental disorders and conditions such as diabetes, obesity and heart disease.

Proper citation: Mouse Mutant Resource (RRID:SCR_008367) Copy   

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http://ophid.utoronto.ca/navigator/

A software package for visualizing and analyzing protein-protein interaction networks. NAViGaTOR can query OPHID / I2D - online databases of interaction data - and display networks in 2D or 3D. To improve scalability and performance, NAViGaTOR combines Java with OpenGL to provide a 2D/3D visualization system on multiple hardware platforms. NAViGaTOR also provides analytical capabilities and supports standard import and export formats such as GO and the Proteomics Standards Initiative (PSI). NAViGaTOR can be installed and run on Microsoft Windows, Linux / UNIX, and Mac OS systems. NAViGaTOR is written in Java and uses JOGL (Java bindings for OpenGL) to support scalability, highlighting or suppressing of information, and other advanced graphic approaches.

Proper citation: Network Analysis, Visualization and Graphing TORonto (RRID:SCR_008373) Copy   

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http://degradome.uniovi.es/diseases.html

This resource has cataloged a total of 80 human hereditary diseases caused by mutations in protease-coding genes, which implies that more than 10% of the human protease genes are involved in human pathologies. They are classified in three groups: loss of function, gain of function, and an heterogeneous group including non-protease homologs (np), putative proteases, and hedgehog proteins with only autoprocessing activity. Type of inheritance is indicated by R (recessive) or D (dominant).

Proper citation: Human Hereditary Diseases of Proteolysis (RRID:SCR_008344) Copy   

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http://www.broad.mit.edu/mammals/dog

The genome of the domesticated dog, a close evolutionary relation to human, is a powerful new tool for understanding the human genome. Comparison of the dog with human and other mammals reveals key information about the structure and evolution of genes and genomes. The unique breeding history of dogs, with their extraordinary behavioral and physical diversity, offers the opportunity to find important genes underlying diseases shared between dogs and humans, such as cancer, diabetes, and epilepsy. The Canine Genome Sequencing Project produced a high-quality draft sequence of a female boxer named Tasha. By comparing Tasha with many other breeds, the project also compiled a comprehensive set of SNPs (single nucleotide polymorphisms) useful in all dog breeds. These closely spaced genomic landmarks are critical for disease mapping. By comparing the dog, rodent, and human lineages, researchers at the Broad Institute uncovered exciting new information about human genes, their evolution, and the regulatory mechanisms governing their expression. Using SNPs, researchers describe the strikingly different haplotype structure in dog breeds compared with the entire dog population. In addition, they show that by understanding the patterns of variation in dog breeds, scientists can design powerful gene mapping experiments for complex diseases that are difficult to map in human populations. Contribute Although the astounding generosity of Eli and Edythe L. Broad and several other venture philanthropists empowers our scientists to tackle many of the most important problems at the cutting edge of genomic medicine, there are many other critical challenges that they cannot yet pursue because of limited resources. We need additional visionary partners to join the Broads and the Broad Institute in transforming medicine with the power of genomics.

Proper citation: Dog Genome Project (RRID:SCR_008486) Copy   

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http://www.broad.mit.edu/cancer/software/genecluster2/gc2.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding supervised classification, gene selection, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting (WV) and k-nearest neighbor (KNN) algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. It enhances the clustering capabilities of GeneCluster 1.0 by adding a module for batch SOM clustering, and also includes a marker gene finder based on a KNN analysis and a visualization module. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.

Proper citation: GeneCluster 2: An Advanced Toolset for Bioarray Analysis (RRID:SCR_008446) Copy   

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http://bdtnp.lbl.gov/Fly-Net/index.jsp?w=home

The goal of this project is to decipher the transcriptional information contained in the extensive cis-acting DNA sequences that direct the patterns of gene expression that underlie animal development. Using the early embryo of the fruitfly Drosophila melanogaster as a model, these researchers are developing experimental and computational methods to systematically characterize and dissect the complex expression patterns and regulatory interactions already present prior to gastrulation. They have identified 37 principal regulatory factors within this network for initial analysis together with their target genes. Sponsors: This project is chiefly funded by a grant from NIGMS and NHGRI, R01 GM070444. Additional funding comes from grants to Michael Eisen, Sue Celniker, and Bernd Hamann.

Proper citation: Berkeley Drosophila Transcription Network Project (RRID:SCR_008640) Copy   

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http://portal.ncibi.org/gateway/gin.html

GIN-IE is a high precision system for extracting protein/gene interactions, interaction cue words, and directionality from the literature. Syntax-aware inferences about the roles of the entities are made by using the syntactic and dependency parse tree structures of the sentences. Negation and speculation are frequently occurring language phenomena that modify the factuality of the information contained in text. GIN-IE detects and distinguishes interactions that are extracted from negated or speculative sentences. GIN-IE has been integrated with the NCIBI PubMed daily update and processing pipeline. The extracted interactions are accessible through MimiWeb.

Proper citation: Gene Interaction Extraction from the Literature (RRID:SCR_008660) Copy   

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Ratings or validation data are available for this resource

http://www.ingenuity.com/products/pathways_analysis.html

A web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.

Proper citation: Ingenuity Pathway Analysis (RRID:SCR_008653) Copy   

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http://rgd.mcw.edu/rgdCuration/?module=portal&func=show&name=nuro

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Portal that provides researchers with easy access to data on rat genes, QTLs, strain models, biological processes and pathways related to neurological diseases. This resource also includes dynamic data analysis tools.

Proper citation: Rat Genome Database: Neurological Disease Portal (RRID:SCR_008685) Copy   

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http://cbdb.nimh.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on February 07, 2013. A multidisciplinary neuroscience laboratory in which basic and clinical scientists work side by side exploring neural mechanisms and models of mental and cognitive function and of neuropsychiatric illness. Experiments are performed at many levels of inquiry, from basic molecular biology of the gene to clinical examinations of patients. A major area of investigation of this laboratory is the genetic mechanisms implicated in the pathogenesis of schizophrenia and its treatment. The laboratory is organized as a multi-disciplinary team of investigators with a common mission: to identify and fully characterize basic genetic and neurobiological mechanisms of schizophrenia and related cognitive and emotional disorders. The various components of this effort are centered various different units or divisions represented by groups of investigators, at various levels of training and experience, working on related experiments. The Director of the Branch and of the Genes, Cognition and Psychosis Program (GCAP) is Daniel R. Weinberger, M.D. The CBDB is the principle research laboratory in the created (2003) Genes, Cognition, and Psychosis Program (GCAP) of the NIMH. After twelve years of residing on the pastoral grounds of St. Elizabeths Hospital, in Southeast Washington, CBDB moved back to the main NIH campus in Bethesda, Maryland in 1998. While the unique setting of St. Elizabeths is irreplaceable, we have occupied beautiful new laboratories and clinic spaces that were created for us, and we are in the mainstream of NIH life., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NIMH Intramural Research Program Clinical Brain Disorders Branch (RRID:SCR_008728) Copy   

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http://dgidb.genome.wustl.edu/

A database of drug-gene relationships that provides drug-gene interactions and potential druggability data given list of genes. There are about 15 data sources that are being aggregated by DGIdb, with update date and these data sources are listed on this page: http://dgidb.genome.wustl.edu/sources, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DGIdb (RRID:SCR_006608) Copy   

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http://www.progenygenetics.com/

Fully customizable, comprehensive genetic pedigree and clinical data management software including a multi-user relational database with an integrated pedigree drawing component to manage genetic and pedigree data in one database. Manage Pedigrees, Individuals, SNPs, STRs, Samples, Plates, Genotypes and exports to multiple analysis platforms. (entry from Genetic Analysis Software) * LIMS software, providing advanced sample tracking and management (including functionality to generate and record barcodes) and configurable workflows for your specific environment. * Full genotype management gives users the ability to track not only family-based studies, but Whole Genome Association studies containing 1000''s of samples with large arrays.

Proper citation: PROGENY (RRID:SCR_006647) Copy   

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http://cellfinder.de/

Database of mapped validated gene and protein expression, phenotype and images related to cell types. The data allow characterization and comparison of cell types and can be browsed by using the body browser and by searching for cells or genes. All cells are related to more complex systems such as tissues, organs and organisms and arranged according to their position in development. CellFinder provides long-term data storage for validated and curated primary research data and provides additional expert-validation through relevant information extracted from text. Operated under the Open Source/Access model, community and scientific networking applications will allow users to store and retrieve their data and to explore cells and their interactions on singular and complex resolution levels. The involvement of stem cell registries and banks will allow direct access to selected cells. The set up the stem cell data repository will involve three lines of action: * the acquisition of scientific data and contents * the standardized description of this data, its organization with the help of ontologies and technical implementation * the integration of existing sources/logistics and to ensure sustainable long-term operation

Proper citation: CellFinder (RRID:SCR_006598) Copy   

•   Source: SciCrunch Registry

http://www.pseudomonas.com/

Database of peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome expanded to include all Pseudomonas species to facilitate cross-strain and cross-species genome comparisons with high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. The current annotation is updated using recent research literature and peer-reviewed submissions by a worldwide community of PseudoCAP (Pseudomonas aeruginosa Community Annotation Project) participating researchers. If you are interested in participating, you are invited to get involved. Many annotations, DNA sequences, Orthologs, Intergenic DNA, and Protein sequences are available for download.

Proper citation: Pseudomonas Genome Database (RRID:SCR_006590) Copy   

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http://www.maizegdb.org

Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.

Proper citation: MaizeGDB (RRID:SCR_006600) Copy   

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http://cancercontrol.cancer.gov/tcrb/tturc/

A transdisciplinary approach to the full spectrum of basic and applied research on tobacco use to reduce the disease burden of tobacco use, including: * Etiology of tobacco use and addiction * Impact of advertising and marketing * Prevention of tobacco use * Treatment of tobacco use and addiction * Identification of biomarkers of tobacco exposure * Identification of genes related to addiction and susceptibility to harm from tobacco Goals * Increase the number of investigators from relevant disciplines who focus on the study of tobacco use as part of transdisciplinary teams. * Generate basic research evidence to improve understanding of the etiology and natural history of tobacco use. * Produce evidence-based tobacco use interventions that can translate to the community and specific understudied or underserved populations. * Increase the number of evidence-based interventions that are novel, including the development, testing and dissemination of innovative behavioral treatments and prevention strategies based upon findings from basic research. * Train transdisciplinary investigators capable of conducting cutting-edge tobacco use research. * Increase the number of peer-reviewed publications in the areas of tobacco use, nicotine addiction, and treatment.

Proper citation: Transdisciplinary Tobacco Use Research Centers (RRID:SCR_006858) Copy   

•   Source: SciCrunch Registry