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http://bejerano.stanford.edu/phenotree/

Web server to search for genes involved in given phenotypic difference between mammalian species. The mouse-referenced multiple alignment data files used to perform the forward genomics screen is also available. The webserver implements one strategy of a Forward Genomics approach aiming at matching phenotype to genotype. Forward genomics matches a given pattern of phenotypic differences between species to genomic differences using a genome-wide screen. In the implementation, the divergence of the coding region of genes in mammals is measured. Given an ancestral phenotypic trait that is lost in independent mammalian lineages, it is shown that searching for genes that are more diverged in all trait-loss species can discover genes that are involved in the given phenotype.

Proper citation: Phenotree (RRID:SCR_003591) Copy   

•   Source: SciCrunch Registry

http://www.mip-dili.eu/

Consortium that brings together Europe's top industrial and academic experts to develop new tests that will help researchers detect potential liver toxicity issues much earlier in drug development, saving many patients from the trauma of liver failure. The team aims to deepen the understanding of the science behind drug-induced liver injury, and use that knowledge to overcome the many drawbacks of the tests currently used. A major focus will be on a systematic and evidence-based evaluation of both currently available and new laboratory test systems, including cultures of liver cells in one-dimensional and three dimensional configurations. The project will also develop models that take into account the natural differences between patients. This is important because factors such as certain genes, the liver's immune response, and viral infections have all been associated with an increased risk of DILI. The project will seek to address the current lack of human liver cells available to researchers by using induced pluripotent stem cells (iPSCs) generated from patients who are particularly sensitive to DILI. Another strand of the project will develop computer models to unravel the complex, often inter-related mechanisms behind DILI. Finally, the team will assess how accurate the results of laboratory tests are at predicting actual outcomes in patients.

Proper citation: MIP-DILI (RRID:SCR_003870) Copy   

•   Source: SciCrunch Registry

http://www.newmeds-europe.com/

Consortium that will develop new models and methods to enable novel treatments for schizophrenia and depression including three important missing tools that will facilitate the translation of scientific findings into benefits for patients. The project will focus on developing new animal models which use brain recording and behavioral tests to identify innovative and effective drugs for schizophrenia. The project will develop standardized paradigms, acquisition and analysis techniques to apply brain imaging, especially fMRI and PET imaging to drug development. It will examine how new genetic findings (duplication and deletion or changes in genes) influence the response to various drugs and whether this information can be used to choose the right drug for the right patient. And finally, it will try and develop new approaches for shorter and more efficient trials of new medication - trials that may require fewer patients and give faster results.

Proper citation: NEWMEDS (RRID:SCR_003872) Copy   

•   Source: SciCrunch Registry

http://www.flexgen.nl/

A biotechnology company that has developed technology for synthesizing custom microarrays, the FlexArrayer. Its is a desk-top sized instrument which allows the researcher to generate, in their own laboratory, either a custom oligonucleotide array in a single day or oligonucleotide pool in a few days. Recent developments in synthesis chemistry allows many modifications to be incorporated or for alternative chemistries to be considered., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: FlexGen (RRID:SCR_003902) Copy   

•   Source: SciCrunch Registry

http://www.agedbrainsysbio.eu/

Consortium focused on identifying the foundational pathways responsible for the aging of the brain, with a focus on Late Onset Alzheimer's disease. They aim to identify the interactions through which the aging phenotype develops in normal and in disease conditions; modeling novel pathways and their evolutionary properties to design experiments that identify druggable targets. As early steps of neurodegenerative disorders are expected to impact synapse function the project will focus in particular on pre- or postsynaptic protein networks. The concept is to identify subsets of pathways with two unique druggable hallmarks, the validation of interactions occurring locally in subregions of neurons and a human and/or primate accelerated evolutionary signature. The consortium will do this through six approaches: * identification of interacting protein networks from recent Late-Onset Alzheimer Disease-Genome Wide Association Studies (LOAD-GWAS) data, * experimental validation of interconnected networks working in subregion of a neuron (such as dendrites and dendritic spines), * inclusion of these experimentally validated networks in larger networks obtained from available databases to extend possible protein interactions, * identification of human and/or primate positive selection either in coding or in regulatory gene sequences, * manipulation of these human and/or primate accelerated evolutionary interacting proteins in human neurons derived from induced Pluripotent Stem Cells (iPSCs) * modeling predictions in drosophila and novel mouse transgenic models * validation of new druggable targets and markers as a proof-of-concept towards the prevention and cure of aging cognitive defects. The scientists will share results and know-how on Late-Onset Alzheimer Disease-Genome Wide Association Studies (LOAD-GWAS) gene discovery, comparative functional genomics in mouse and drosophila models, in mouse transgenic approaches, research on human induced pluripotent stem cells (hiPSC) and their differentiation in vitro and modeling pathways with emphasis on comparative and evolutionary aspects. The four European small to medium size enterprises (SMEs) involved will bring their complementary expertise and will ensure translation of project results to clinical application.

Proper citation: AgedBrainSYSBIO (RRID:SCR_003825) Copy   

•   Source: SciCrunch Registry

https://www.bioshare.eu/

A consortium of leading biobanks and international researchers from all domains of biobanking science to ensure the development of harmonized measures and standardized computing infrastructures enabling the effective pooling of data and key measures of life-style, social circumstances and environment, as well as critical sub-components of the phenotypes associated with common complex diseases. The overall aim is to build upon tools and methods available to achieve solutions for researchers to use pooled data from different cohort and biobank studies. This, in order to obtain the very large sample sizes needed to investigate current questions in multifactorial diseases, notably on gene-environment interactions. This aim will be achieved through the development of harmonization and standardization tools, implementation of these tools and demonstration of their applicability. BioSHaRE researchers are collaborating with P3G, the Global Alliance for Genomics and Health, IRDiRC (International Rare Diseases Research Consortium), H3Africa and other organizations on the development of an International Code of Conduct for Genomic and Health-Related Data Sharing. A draft version is available for external review. Generic documents have been prepared covering areas of biobanking that are of major importance. SOPs have been finalized for blood withdrawal (SOPWP5001blood withdrawal), manual blood processing (SOPWP5002blood processing), shipping of biosamples (SOPWP5003shipping) and withdrawal, processing and storage of urine samples (SOPWP5004urine).

Proper citation: BioSHaRE (RRID:SCR_003811) Copy   

•   Source: SciCrunch Registry

http://clinicaltrials.gov/show/NCT01211678

A consortium evaluating a new biomarker screening test that might help identify patients with rheumatoid arthritis (RA) who are unlikely to benefit from anti-tumor necrosis factor-alpha (TNFalpha) medications. BATTER-UP will enroll around 1,000 patients being treated by one of several marketed anti-TNF RA drugs: Enbrel, Remicade, Humira, Simponi, or Cimzia. Through data analyses and predictive response modeling, the consortium aims to better understand which patients with RA will derive the greatest benefit from TNF inhibitors. The investigators in this observational study will attempt to validate an 8-gene biomarker set based on work by Biogen Idec researchers as likely to predict anti-TNF responsiveness in patients with RA. In preliminary results, the 8-gene biomarker set predicted with 89% accuracy individuals who did not reach European League Against Rheumatism (EULAR) Disease Activity Score (DAS)-28 good response after 14 weeks of treatment. The 8 genes included in the screen are CLTB, MXRA7, CXorf52, COL4A3BP, YIPF6, FAM44A, SFRS2, and PGK1. Biological samples and clinical outcome information will be used to confirm and extend the utility of previously published biomarkers that can predict response to anti-TNF agents. These data may also generate new hypotheses for further testing. The BATTER-UP samples and data will be established as a reference set for investigation of personalized medicine in RA. The study will be a resource of DNA and other biological materials that can be investigated for biomarkers in the future as new technologies arise.

Proper citation: Biomarkers of Anti-TNF Treatment Efficacy in Rheumatoid Arthritis - Unresponsive Populations (RRID:SCR_004019) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/edgeR/

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

Proper citation: edgeR (RRID:SCR_012802) Copy   

•   Source: SciCrunch Registry

http://www.kegg.jp/

Integrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.

Proper citation: KEGG (RRID:SCR_012773) Copy   

•   Source: SciCrunch Registry

http://gmod.org/wiki/Flash_GViewer

Flash GViewer is a customizable Flash movie that can be easily inserted into a web page to display each chromosome in a genome along with the locations of individual features on the chromosomes. It is intended to provide an overview of the genomic locations of a specific set of features - eg. genes and QTLs associated with a specific phenotype, etc. rather than as a way to view all features on the genome. The features can hyperlink out to a detail page to enable to GViewer to be used as a navigation tool. In addition the bands on the chromosomes can link to defineable URL and new region selection sliders can be used to select a specific chromosome region and then link out to a genome browser for higher resolution information. Genome maps for Rat, Mouse, Human and C. elegans are provided but other genome maps can be easily created. Annotation data can be provided as static text files or produced as XML via server scripts. This tool is not GO-specific, but was built for the purpose of viewing GO annotation data. Platform: Online tool

Proper citation: Flash Gviewer (RRID:SCR_012870) Copy   

•   Source: SciCrunch Registry

http://www.zebrafinchatlas.org

Expression atlas of in situ hybridization images from large collection of genes expressed in brain of adult male zebra finches. Goal of ZEBrA project is to develop publicly available on-line digital atlas that documents expression of large collection of genes within brain of adult male zebra finches.

Proper citation: Zebra Finch Expression Brain Atlas (RRID:SCR_012988) Copy   

•   Source: SciCrunch Registry

http://www.viprbrc.org/brc/home.do?decorator=vipr

Provides searchable public repository of genomic, proteomic and other research data for different strains of pathogenic viruses along with suite of tools for analyzing data. Data can be shared, aggregated, analyzed using ViPR tools, and downloaded for local analysis. ViPR is an NIAID-funded resource that support the research of viral pathogens in the NIAID Category A-C Priority Pathogen lists and those causing (re)emerging infectious diseases. It provides a dedicated gateway to SARS-CoV-2 data that integrates data from external sources (GenBank, UniProt, Immune Epitope Database, Protein Data Bank), direct submissions, analysis pipelines and expert curation, and provides a suite of bioinformatics analysis and visualization tools for virology research.

Proper citation: Virus Pathogen Resource (ViPR) (RRID:SCR_012983) Copy   

•   Source: SciCrunch Registry

http://www.genesigdb.org

Database of traceable, standardized, annotated gene signatures which have been manually curated from publications that are indexed in PubMed. The Advanced Gene Search will perform a One-tailed Fisher Exact Test (which is equivalent to Hypergeometric Distribution) to test if your gene list is over-represented in any gene signature in GeneSigDB. Gene expression studies typically result in a list of genes (gene signature) which reflect the many biological pathways that are concurrently active. We have created a Gene Signature Data Base (GeneSigDB) of published gene expression signatures or gene sets which we have manually extracted from published literature. GeneSigDB was creating following a thorough search of PubMed using defined set of cancer gene signature search terms. We would be delighted to accept or update your gene signature. Please fill out the form as best you can. We will contact you when we get it and will be happy to work with you to ensure we accurately report your signature. GeneSigDB is capable of providing its functionality through a Java RESTful web service.

Proper citation: GeneSigDB (RRID:SCR_013275) Copy   

•   Source: SciCrunch Registry

http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.ust.hk/BOOST.html

Software application (entry from Genetic Analysis Software) for a method for detecting gene-gene interactions. It allows examining all pairwise interactions in genome-wide case-control studies.

Proper citation: BOOST (RRID:SCR_013133) Copy   

•   Source: SciCrunch Registry

http://www-sequence.stanford.edu/group/candida/

The Stanford Genome Technology Center began a whole genome shotgun sequencing of strain SC5314 of Candida albicans. After reaching its original goal of 1.5X mean coverage of the haploid genome (16Mb) in summer, 1998, Stanford was awarded a supplemental grant to continue sequencing up to a coverage of 10X, performing as much assembly of the sequence as possible, using recognizable genes as nucleation points. Candida albicans is one of the most commonly encountered human pathogens, causing a wide variety of infections ranging from mucosal infections in generally healthy persons to life-threatening systemic infections in individuals with impaired immunity. Oral and esophogeal Candida infections are frequently seen in AIDS patients. Few classes of drugs are effective against these fungal infections, and all of them have limitations with regard to efficacy and side-effects.

Proper citation: Sequencing of Candida Albicans (RRID:SCR_013437) Copy   

•   Source: SciCrunch Registry

https://omictools.com/l2l-tool

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 26, 2019.

Database of published microarray gene expression data, and a software tool for comparing that published data to a user''''s own microarray results. It is very simple to use - all you need is a web browser and a list of the probes that went up or down in your experiment. If you find L2L useful please consider contributing your published data to the L2L Microarray Database in the form of list files. L2L finds true biological patterns in gene expression data by systematically comparing your own list of genes to lists of genes that have been experimentally determined to be co-expressed in response to a particular stimulus - in other words, published lists of microarray results. The patterns it finds can point to the underlying disease process or affected molecular function that actually generated the observed changed in gene expression. Its insights are far more systematic than critical gene analyses, and more biologically relevant than pure Gene Ontology-based analyses. The publications included in the L2L MDB initially reflected topics thought to be related to Cockayne syndrome: aging, cancer, and DNA damage. Since then, the scope of the publications included has expanded considerably, to include chromatin structure, immune and inflammatory mediators, the hypoxic response, adipogenesis, growth factors, hormones, cell cycle regulators, and others. Despite the parochial origins of the database, the wide range of topics covered will make L2L of general interest to any investigator using microarrays to study human biology. In addition to the L2L Microarray Database, L2L contains three sets of lists derived from Gene Ontology categories: Biological Process, Cellular Component, and Molecular Function. As with the L2L MDB, each GO sub-category is represented by a text file that contains annotation information and a list of the HUGO symbols of the genes assigned to that sub-category or any of its descendants. You don''''t need to download L2L to use it to analyze your microarray data. There is an easy-to-use web-based analysis tool, and you have the option of downloading your results so you can view them at any time on your own computer, using any web browser. However, if you prefer, the entire L2L project, and all of its components, can be downloaded from the download page. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: L2L Microarray Analysis Tool (RRID:SCR_013440) Copy   

•   Source: SciCrunch Registry

http://PlasmoDB.org

Functional genomic database for malaria parasites. Database for Plasmodium spp. Provides resource for data analysis and visualization in gene-by-gene or genome-wide scale. PlasmoDB 5.5 contains annotated genomes, evidence of transcription, proteomics evidence, protein function evidence, population biology and evolution data. Data can be queried by selecting from query grid or drop down menus. Results can be combined with each other on query history page. Search results can be downloaded with associated functional data and registered users can store their query history for future retrieval or analysis.Key community database for malaria researchers, intersecting many types of laboratory and computational data, aggregated by gene.

Proper citation: PlasmoDB (RRID:SCR_013331) Copy   

•   Source: SciCrunch Registry

http://www.nabc.go.kr/sgd/

Database for ESTs (Expressed Sequence Tags), consensus sequences, bacterial artificial chromosome (BAC) clones, BES (BAC End Sequences). They have generated 69,545 ESTs from 6 full-length cDNA libraries (Porcine Abdominal Fat, Porcine Fat Cell, Porcine Loin Muscle, Liver and Pituitary gland). They have also identified a total of 182 BAC contigs from chromosome 6. It is very valuable resources to study porcine quantitative trait loci (QTL) mapping and genome study. Users can explore genomic alignment of various data types, including expressed sequence tags (ESTs), consensus sequences, singletons, QTL, Marker, UniGene and BAC clones by several options. To estimate the genomic location of sequence dataset, their data aligned BES (BAC End Sequences) instead of genomic sequence because Pig Genome has low-coverage sequencing data. Sus scrofa Genome Database mainly provide comparative map of four species (pig, cattle, dog and mouse) in chromosome 6.

Proper citation: PiGenome (RRID:SCR_013394) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.psb.ugent.be/ENIGMA/

A software tool to extract gene expression modules from perturbational microarray data, based on the use of combinatorial statistics and graph-based clustering. The modules are further characterized by incorporating other data types, e.g. GO annotation, protein interactions and transcription factor binding information, and by suggesting regulators that might have an effect on the expression of (some of) the genes in the module. Version : ENIGMA 1.1 used GO annotation version : Aug 29th 2007

Proper citation: ENIGMA (RRID:SCR_013400) Copy   

•   Source: SciCrunch Registry