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http://www.gene-regulation.com/pub/databases.html#transpath

Database on eukaryotic transcription factors, their experimentally-proven binding sites, consensus binding sequences (positional weight matrices) and regulated genes. Its broad compilation of binding sites allows the derivation of positional weight matrices. It can either be used as an encyclopedia, for both specific and general information on signal transduction, or can serve as a network analyzer. Cross-references to important sequence and signature databases such as EMBL/GenBank UniProt/Swiss-Prot InterPro or Ensembl EntrezGene RefSeq are provided. The database is equipped with the tools for data visualization and analysis. It has three modules: the first one is the data, which have been manually extracted, mostly from the primary literature; the second is PathwayBuilder, which provides several different types of network visualization and hence facilitates understanding; the third is ArrayAnalyzer, which is particularly suited to gene expression array interpretation, and is able to identify key molecules within signalling networks (potential drug targets). These key molecules could be responsible for the coordinated regulation of downstream events. Manual data extraction focuses on direct reactions between signalling molecules and the experimental evidence for them, including species of genes/proteins used in individual experiments, experimental systems, materials and methods. This combination of materials and methods is used in TRANSPATH to assign a quality value to each experimentally proven reaction, which reflects the probability that this reaction would happen under physiological conditions. Another important feature in TRANSPATH is the inclusion of transcription factor-gene relations, which are transferred from TRANSFAC, a database focused on transcription regulation and transcription factors. Since interactions between molecules are mainly direct, this allows a complete and stepwise pathway reconstruction from ligands to regulated genes.

Proper citation: TRANSPATH (RRID:SCR_005640) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/Tools/pfa/iprscan/

Software package for functional analysis of sequences by classifying them into families and predicting presence of domains and sites. Scans sequences against InterPro's signatures. Characterizes nucleotide or protein function by matching it with models from several different databases. Used in large scale analysis of whole proteomes, genomes and metagenomes. Available as Web based version and standalone Perl version and SOAP Web Service.

Proper citation: InterProScan (RRID:SCR_005829) Copy   

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http://www.gotaxexplorer.de/

GOTaxExplorer presents a new approach to comparative genomics that integrates functional information and families with the taxonomic classification. It integrates UniProt, Gene Ontology, NCBI Taxonomy, Pfam and SMART in one database. GOTaxExplorer provides four different query types: selection of entity sets, comparison of sets of Pfam families, semantic comparison of sets of GO terms, functional comparison of sets of gene products. This permits to select custom sets of GO terms, families or taxonomic groups. For example, it is possible to compare arbitrarily selected organisms or groups of organisms from the taxonomic tree on the basis of the functionality of their genes. Furthermore, it enables to determine the distribution of specific molecular functions or protein families in the taxonomy. The comparison of sets of GO terms allows to assess the semantic similarity of two different GO terms. The functional comparison of gene products makes it possible to identify functionally equivalent and functionally related gene products from two organisms on the basis of GO annotations and a semantic similarity measure for GO. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GOTaxExplorer (RRID:SCR_005720) Copy   

•   Source: SciCrunch Registry

http://vibez.informatik.uni-freiburg.de/

An imaging and image analysis framework for virtual colocalization studies in larval zebrafish brains, currently available for 72hpf, 48hpf and 96hpf old larvae. ViBE-Z contains a database with precisely aligned gene expression patterns (1����m^3 resolution), an anatomical atlas, and a software. This software creates high-quality data sets by fusing multiple confocal microscopic image stacks, and aligns these data sets to the standard larva. The ViBE-Z database and atlas are stored in HDF5 file format. They are freely available for download. ViBE-Z provides a software that automatically maps gene expression data with cellular resolution to a 3D standard larval zebrafish (Danio rerio) brain. ViBE-Z enhances the data quality through fusion and attenuation correction of multiple confocal microscope stacks per specimen and uses a fluorescent stain of cell nuclei for image registration. It automatically detects 14 predefined anatomical landmarks for aligning new data with the reference brain. ViBE-Z performs colocalization analysis in expression databases for anatomical domains or subdomains defined by any specific pattern. The ViBE-Z database, atlas and software are provided via a web interface.

Proper citation: ViBE-Z (RRID:SCR_005895) Copy   

•   Source: SciCrunch Registry

http://www.livinghuman.org/

Distributed repository of anatomo-functional data and of simulation algorithms, fully integrated into a seamless simulation environment and directly accessible. This infrastructure will be used to create the physiome of the human musculo-skeletal system.

Proper citation: LHP LHDL (RRID:SCR_005928) Copy   

•   Source: SciCrunch Registry

http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

https://www.infrafrontier.eu/emma/

Non-profit repository for the collection, archiving (via cryopreservation) and distribution of relevant mutant strains essential for basic biomedical research. Users may browse by strain, gene, phenotype, or human disease. Its primary objective is to establish and manage a unified repository for maintaining medically relevant mouse mutants and making them available to the scientific community. Therefore, EMMA archives mutant strains and distributes them to requesting researchers. EMMA also hosts courses in cryopreservation, to promote the use and dissemination of frozen embryos and spermatozoa. Dissemination of knowledge is further fostered by a dedicated resource database. Anybody who wants their mutant mouse strains cryopreserved may deposit strains with EMMA. However depositors must be aware that these strains become freely available to other researchers after being deposited.With more than 8400 mutant mouse strains and asmall but increasing number of rat mutant strains available, EMMA is the primary mouse repository in Europe and the third largest non-profit repository worldwide.

Proper citation: European Mouse Mutant Archive (RRID:SCR_006136) Copy   

•   Source: SciCrunch Registry

https://vdjbase.org/

Open source adaptive immune receptor genotype and haplotype database. Core collection is inferred from immune receptor repertoire sequences and genomically derived material. Provides customisable reports, which allow users to study gene and allele usage in various ways.

Proper citation: VDJbase (RRID:SCR_022599) Copy   

•   Source: SciCrunch Registry

http://data-analysis.charite.de/care/

Comprehensive database of cancer relevant proteins and compound interactions supported by experimental knowledge.Knowledgebase for drug-target relationships related to cancer as well as for supporting information or experimental data.

Proper citation: CancerResource (RRID:SCR_011945) Copy   

•   Source: SciCrunch Registry

https://juaml.github.io/julearn

Software library of easy testing ML models directly from pandas DataFrames, while keeping the flexibility of using scikit-learn’s models.

Proper citation: Julearn (RRID:SCR_024881) Copy   

•   Source: SciCrunch Registry

http://starnet.mssm.edu/

Web interactive browser to visualize data and perform gene set enrichment analysis along with gene and SNP lookup. Web interface used to query STARNET datasets and downstream analysis which includes RNAseq from 7 tissues: blood, free internal mammary artery (MAM), atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV). Paired SNP genotyping data is included and utilized for tissue expression quantitative trait loci (eQTL), CAD heritability (H2), co-expression networks and gene regulatory networks.

Proper citation: STARNET (RRID:SCR_025238) Copy   

•   Source: SciCrunch Registry

https://pathogens.no

Portal provides information about available datasets, resources, tools, and services related to pandemic preparedness in Norway. Portal gives researchers, clinicians and policymakers access to collection of biomolecular data about pathogens.

Proper citation: Pathogens Portal Norway (RRID:SCR_025641) Copy   

•   Source: SciCrunch Registry

http://www.alzheimer-europe.org/

A non-governmental organization aimed at raising awareness of all forms of dementia by creating a common European platform through co-ordination and co-operation between Alzheimer organizations throughout Europe. Alzheimer Europe is also a source of information on all aspects of dementia.

Proper citation: Alzheimer Europe (RRID:SCR_003802) Copy   

•   Source: SciCrunch Registry

https://github.com/INCF/csa

Software tool for description of connectivity in small and large scale neuronal network models. It provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. Can be used as component of neuronal network simulators or other tools.

Proper citation: Connection-set algebra (RRID:SCR_017397) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

•   Source: SciCrunch Registry

http://abacas.sourceforge.net

Software that contiguates (align, order, orientate), visualizes and designs primers to close gaps on shotgun assembled contigs based on a reference sequence. ABACAS finds alignment positions and identifies syntenies of assembled contigs against the reference, then generates a pseudomolecule taking overlapping contigs and gaps into account.

Proper citation: ABACAS (RRID:SCR_015852) Copy   

•   Source: SciCrunch Registry

http://www.chernobyltissuebank.com/

The CTB (Chernobyl Tissue Bank) is an international cooperation that collects, stores and disseminates biological samples from tumors and normal tissues from patients for whom the aetiology of their disease is known - exposure to radioiodine in childhood following the accident at the Chernobyl power plant. The main objective of this project is to provide a research resource for both ongoing and future studies of the health consequences of the Chernobyl accident. It seeks to maximize the amount of information obtained from small pieces of tumor by providing multiple aliquots of RNA and DNA extracted from well documented pathological specimens to a number of researchers world-wide and to conserve this valuable material for future generations of scientists. It exists to promote collaborative, rather than competitive, research on a limited biological resource. Tissue is collected to an approved standard operating procedure (SOP) and is snap frozen; the presence or absence of tumor is verified by frozen section. A representative paraffin block is also obtained for each case. Where appropriate, we also collect fresh and paraffin-embedded tissue from loco-regional metastases. Currently we do not issue tissue but provide extracted nucleic acid, paraffin sections and sections from tissue microarrays from this material. The project is coordinated from Imperial College, London and works with Institutes in the Russian Federation (the Medical Radiological Research Centre in Obninsk) and Ukraine (the Institute of Endocrinology and Metabolism in Kiev) to support local scientists and clinicians to manage and run a tissue bank for those patients who have developed thyroid tumors following exposure to radiation from the Chernobyl accident. Belarus was also initially included in the project, but is currently suspended for political reasons.

Proper citation: Chernobyl Tissue Bank (RRID:SCR_010662) Copy   

•   Source: SciCrunch Registry

https://github.com/farkkilab/tribus

Software tool for cell type based analysis of multiplexed imaging data. Interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. Recovers fine-grained cell types, matching the gold standard annotations by human experts, can target ambiguous populations and discover phenotypically distinct cell subtypes.

Proper citation: TRIBUS (RRID:SCR_027367) Copy   

•   Source: SciCrunch Registry

http://hcsquared.eu/home

HC2 is an EU funded project that aims to promote, support and help define future lines of research in Human Computer Confluence (HCC). HCC is the study of the intersection of HCI, Cognitive Neuroscience, VR/AR, Presence, Pervasive Computing and how they can enable new forms of sensing, perception, interaction and understanding. In a sense it is the study of the disappearing interface. HCC, Human-Computer Confluence, is an ambitious research program studying how the emerging symbiotic relation between humans and computing devices can enable radically new forms of sensing, perception, interaction, and understanding. The horizontal character of HCC makes it a fascinating and fertile interdisciplinary field, but it can also compromise its growth, with researchers scattered across disciplines and groups worldwide. To address this we are building a community of HCC researchers. There are lots of ways you can join in. Add your name to the HCC Players Map, take advantage of our Exchange Program to work with colleagues at your favorite lab, sign up for our Summer School or just follow us on Twitter and LinkedIn to see what''s happening. In order to foster interdisciplinary research and promote HCC research we have set up an Exchange Program. Students that wish to apply for financial support from our Exchange Program should follow the steps provided. The Exchange Program is open to all graduate students (Masters and PhD). A maximum of 500 Euro support will be provided per student.

Proper citation: HC2: Human-Computer Confluence (RRID:SCR_005549) Copy   

•   Source: SciCrunch Registry

https://lsbr.niams.nih.gov/bsoft/

Software package and a platform for the processing of electron micrographs in structural biology. Supports different image file formats used in electron microscopy (including MRC, SPIDER, IMAGIC, SUPRIM, and PIF)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bsoft (RRID:SCR_016503) Copy   

•   Source: SciCrunch Registry