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http://developingmouse.brain-map.org/

Map of gene expression in developing mouse brain revealing gene expression patterns from embryonic through postnatal stages. Provides information about spatial and temporal regulation of gene expression with database. Feature include seven sagittal reference atlases created with a developmental ontology. These anatomic atlases may be viewed alongside in situ hybridization (ISH) data as well as by itself.

Proper citation: Allen Developing Mouse Brain Atlas (RRID:SCR_002990) Copy   

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http://deweylab.biostat.wisc.edu/rsem/

Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.

Proper citation: RSEM (RRID:SCR_000262) Copy   

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http://cran.r-project.org/src/contrib/Archive/iFad/

An R software package implementing a bayesian sparse factor model for the joint analysis of paired datasets, the gene expression and drug sensitivity profiles, measured across the same panel of samples, e.g. cell lines.

Proper citation: iFad (RRID:SCR_000271) Copy   

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http://discover.nci.nih.gov/gominer/GoCommandWebInterface.jsp

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. A web program that organizes lists of genes of interest (for example, under- and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology and automates the analysis of multiple microarrays then integrates the results across all of them in exportable output files and visualizations. High-Throughput GoMiner is an enhancement of GoMiner and is implemented with both a command line interface and a web interface. The program can also: efficiently perform automated batch processing of an arbitrary number of microarrays; produce a human- or computer-readable report that rank-orders the multiple microarray results according to the number of significant GO categories; integrate the multiple microarray results by providing organized, global clustered image map visualizations of the relationships of significant GO categories; provide a fast form of false discovery rate multiple comparisons calculation; and provide annotations and visualizations for relating transcription factor binding sites to genes and GO categories.

Proper citation: High-Throughput GoMiner (RRID:SCR_000173) Copy   

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http://icbi.at/software/gpviz/gpviz.shtml

A versatile Java-based software used for dynamic gene-centered visualization of genomic regions and/or variants.

Proper citation: GPViz (RRID:SCR_000346) Copy   

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http://teddy.epi.usf.edu/

International consortium of six centers assembled to participate in the development and implementation of studies to identify infectious agents, dietary factors, or other environmental agents, including psychosocial factors, that trigger type 1 diabetes in genetically susceptible people. The coordinating centers recruit and enroll subjects, obtaining informed consent from parents prior to or shortly after birth, genetic and other types of samples from neonates and parents, and prospectively following selected neonates throughout childhood or until development of islet autoimmunity or T1DM. The study tracks child diet, illnesses, allergies and other life experiences. A blood sample is taken from children every 3 months for 4 years. After 4 years, children will be seen every 6 months until the age of 15 years. Children are tested for 3 different autoantibodies. The study will compare the life experiences and blood and stool tests of the children who get autoantibodies and diabetes with some of those children who do not get autoantibodies or diabetes. In this way the study hopes to find the triggers of T1DM in children with higher risk genes.

Proper citation: TEDDY (RRID:SCR_000383) Copy   

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http://www.arb-home.de/

Software environment for maintaining databases of molecular sequences and additional information, and for analyzing the sequence data, with emphasis on phylogeny reconstruction. Programs have primarily been developed for ribosomal ribonucleic acid (rRNA) sequences and, therefore, contain special tools for alignment and analysis of these structures. However, other molecular sequence data can also be handled. Protein gene sequences and predicted protein primary structures as well as protein secondary structures can be stored in the same database. ARB package is designed for graphical user interface. Program control and data display are available in a hierarchical set of windows and subwindows. Majority of operations can be controlled using mouse for moving pointer and the left mouse button for initiating and performing operations.

Proper citation: ARB project (RRID:SCR_000515) Copy   

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http://fulxie.0fees.us/?type=reference&ckattempt=1

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1,2023. Web-based tool for evaluating and screening reference genes from extensive experimental datasets. It integrates major computational programs (geNorm, Normfinder, BestKeeper, and the comparative delta-Ct method) to compare and rank the tested candidate reference genes. Based on the rankings from each program, it assigns an appropriate weight to an individual gene and calculated the geometric mean of their weights for the overall final ranking., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RefFinder (RRID:SCR_000472) Copy   

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http://www.flybrain.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Interactive database of Drosophila melanogaster nervous system. Used by drosophila neuroscience community and by other researchers studying arthropod brain structure.

Proper citation: FlyBrain (RRID:SCR_000706) Copy   

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http://www.psb.ugent.be/esb/PiNGO/

A Java-based tool to easily find unknown genes in a network that are significantly associated with user-defined target Gene Ontology (GO) categories. PiNGO is implemented as a plugin for Cytoscape, a popular open source software platform for visualizing and integrating molecular interaction networks. PiNGO predicts the categorization of a gene based on the annotations of its neighbors, using the enrichment statistics of its sister tool BiNGO. Networks can either be selected from the Cytoscape interface or uploaded from file. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: PiNGO (RRID:SCR_000692) Copy   

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http://franklin.imgen.bcm.tmc.edu/

The mission of the Baylor College of Medicine - Shaw Laboratory is to apply methods of statistics and bioinformatics to the analysis of large scale genomic data. Our vision is data integration to reveal the underlying connections between genes and processes in order to cure disease and improve healthcare.

Proper citation: Baylor College of Medicine - Shaw Laboratory (RRID:SCR_000604) Copy   

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http://gdm.fmrp.usp.br/

Laboratory portal of the University of Sao Paulo Molecular Genetics and Bioinformatic Laboratory.

Proper citation: USP Molecular Genetics and Bioinformatics Laboratory (RRID:SCR_000605) Copy   

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http://harvard.eagle-i.net/i/0000012e-58c7-d44f-55da-381e80000000

Core to provide gene expression data analysis service. Activities range from the provision of services to fully collaborative grant funded investigations.

Proper citation: Harvard Partners HealthCare Center for Personalized Genetic Medicine Bioinformatics Core Facility (RRID:SCR_000882) Copy   

•   Source: SciCrunch Registry

http://www.yandell-lab.org/software/index.html

Sequenced genomes contain a treasure trove of information about how genes function and evolve. Getting at this information, however, is challenging and requires novel approaches that combine computer science and experimental molecular biology. My lab works at the intersection of both domains, and research in our group can be summarized as follows: generate hypotheses concerning gene function and evolution by computational means, and then test these hypotheses at the bench. This is easier said than done, as serious barriers still exist to using sequenced genomes and their annotations as starting points for experimental work. Some of these barriers lie in the computational domain, others in the experimental. Though challenging, overcoming these barriers offers exciting training opportunities in both computer science and molecular genetics, especially for those seeking a future at the intersection of both fields. Ongoing projects in the lab are centered on genome annotation and comparative genomics; exploring the relationships between sequence variation and human disease; and high-throughput biological image analysis. Current software tools available: VAAST (the Variant Annotation, Analysis & Search Tool) is a probabilistic search tool for identifying damaged genes and their disease-causing variants in personal genome sequences. VAAST builds upon existing amino acid substitution (AAS) and aggregative approaches to variant prioritization, combining elements of both into a single unified likelihood-framework that allows users to identify damaged genes and deleterious variants with greater accuracy, and in an easy-to-use fashion. VAAST can score both coding and non-coding variants, evaluating the cumulative impact of both types of variants simultaneously. VAAST can identify rare variants causing rare genetic diseases, and it can also use both rare and common variants to identify genes responsible for common diseases. VAAST thus has a much greater scope of use than any existing methodology. MAKER 2 (updated 01-16-2012) MAKER is a portable and easily configurable genome annotation pipeline. It's purpose is to allow smaller eukaryotic and prokaryotic genomeprojects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values. MAKER is also easily trainable: outputs of preliminary runs can be used to automatically retrain its gene prediction algorithm, producing higher quality gene-models on seusequent runs. MAKER's inputs are minimal and its ouputs can be directly loaded into a GMOD database. They can also be viewed in the Apollo genome browser; this feature of MAKER provides an easy means to annotate, view and edit individual contigs and BACs without the overhead of a database. MAKER should prove especially useful for emerging model organism projects with minimal bioinformatics expertise and computer resources. RepeatRunner RepeatRunner is a CGL-based program that integrates RepeatMasker with BLASTX to provide a comprehensive means of identifying repetitive elements. Because RepeatMasker identifies repeats by means of similarity to a nucleotide library of known repeats, it often fails to identify highly divergent repeats and divergent portions of repeats, especially near repeat edges. To remedy this problem, RepeatRunner uses BLASTX to search a database of repeat encoded proteins (reverse transcriptases, gag, env, etc...). Because protein homologies can be detected across larger phylogenetic distances than nucleotide similarities, this BLASTX search allows RepeatRunner to identify divergent protein coding portions of retro-elements and retro-viruses not detected by RepeatMasker. RepeatRunner merges its BLASTX and RepeatMasker results to produce a single, comprehensive XML-based output. It also masks the input sequence appropriately. In practice RepeatRunner has been shown to greatly improve the efficacy of repeat identifcation. RepeatRunner can also be used in conjunction with PILER-DF - a program designed to identify novel repeats - and RepeatMasker to produce a comprehensive system for repeat identification, characterization, and masking in the newly sequenced genomes. CGL CGL is a software library designed to facilitate the use of genome annotations as substrates for computation and experimentation; we call it CGL, an acronym for Comparitive Genomics Library, and pronounce it Seagull. The purpose of CGL is to provide an informatics infrastructure for a laboratory, department, or research institute engaged in the large-scale analysis of genomes and their annotations.

Proper citation: Yandell Lab Portal (RRID:SCR_000807) Copy   

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http://www.rostlab.org/cms/

A lab organization which has bases in Munich, Germany and at Columbia University and focuses its research on protein structure and function using sequence and evolutionary information. They utilize machine learning and statistical methods to analyze genetic material and its gene products. Research goals of the lab involve using protein and DNA sequences along with evolutionary information to predict aspects of the proteins relevant to the advance of biomedical research.

Proper citation: ROSTLAB (RRID:SCR_000792) Copy   

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http://fantom.gsc.riken.jp/

International collaborative research project and database of annotated mammalian genome. Used to improve estimates of total number of genes and their alternative transcript isoforms in both human and mouse. Consortium to assign functional annotations to full length cDNAs that were collected during Mouse Encyclopedia Project at RIKEN.

Proper citation: Functional Annotation of the Mammalian Genome (RRID:SCR_000788) Copy   

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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.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