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http://www.evidenceontology.org

A controlled vocabulary that describes types of scientific evidence within the realm of biological research that can arise from laboratory experiments, computational methods, manual literature curation, and other means. Researchers can use these types of evidence to support assertions about research subjects that result from scientific research, such as scientific conclusions, gene annotations, or other statements of fact. ECO comprises two high-level classes, evidence and assertion method, where evidence is defined as a type of information that is used to support an assertion, and assertion method is defined as a means by which a statement is made about an entity. Together evidence and assertion method can be combined to describe both the support for an assertion and whether that assertion was made by a human being or a computer. However, ECO can not be used to make the assertion itself; for that, one would use another ontology, free text description, or other means. ECO was originally created around the year 2000 to support gene product annotation by the Gene Ontology. Today ECO is used by many groups concerned with provenance in scientific research. ECO is used in AmiGO 2

Proper citation: ECO (RRID:SCR_002477) Copy   

•   Source: SciCrunch Registry

http://itools.loni.usc.edu/

An infrastructure for managing of diverse computational biology resources - data, software tools and web-services. The iTools design, implementation and meta-data content reflect the broad NCBC needs and expertise (www.NCBCs.org).

Proper citation: iTools (RRID:SCR_009626) Copy   

•   Source: SciCrunch Registry

http://weblogo.berkeley.edu

Web application to generate sequence logos, graphical representations of patterns within multiple sequence alignment. Designed to make generation of sequence logos easy. Sequence logo generator.

Proper citation: WEBLOGO (RRID:SCR_010236) Copy   

•   Source: SciCrunch Registry

http://homer.ucsd.edu/

Software tools for Motif Discovery and next-gen sequencing analysis. Used for analyzing ChIP-Seq, GRO-Seq, RNA-Seq, DNase-Seq, Hi-C and numerous other types of functional genomics sequencing data sets. Collection of command line programs for unix style operating systems written in Perl and C++.

Proper citation: HOMER (RRID:SCR_010881) 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.genmapp.org/

GenMAPP is a free computer application designed to visualize gene expression and other genomic data on maps representing biological pathways and groupings of genes. Integrated with GenMAPP are programs to perform a global analysis of gene expression or genomic data in the context of hundreds of pathway MAPPs and thousands of Gene Ontology Terms (MAPPFinder), import lists of genes/proteins to build new MAPPs (MAPPBuilder), and export archives of MAPPs and expression/genomic data to the web. The main features underlying GenMAPP are: *Draw pathways with easy to use graphics tools *Color genes on MAPP files based on user-imported genomic data *Query data against MAPPs and the GeneOntology Enhanced features include the simultaneous view of multiple color sets, expanded species-specific gene databases and custom database options.

Proper citation: Gene Map Annotator and Pathway Profiler (RRID:SCR_005094) Copy   

•   Source: SciCrunch Registry

http://pdbml.pdb.org/

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

Proper citation: Protein Data Bank Markup Language (RRID:SCR_005085) Copy   

•   Source: SciCrunch Registry

http://bowtie-bio.sourceforge.net/index.shtml

Software ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.

Proper citation: Bowtie (RRID:SCR_005476) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://evolution.genetics.washington.edu/phylip.html

A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.

Proper citation: PHYLIP (RRID:SCR_006244) Copy   

•   Source: SciCrunch Registry

http://stormo.wustl.edu/ScerTF

Catalog of over 1,200 position weight matrices (PWMs) for 196 different yeast transcription factors (TFs). They've curated 11 literature sources, benchmarked the published position-specific scoring matrices against in-vivo TF occupancy data and TF deletion experiments, and combined the most accurate models to produce a single collection of the best performing weight matrices for Saccharomyces cerevisiae. ScerTF is useful for a wide range of problems, such as linking regulatory sites with transcription factors, identifying a transcription factor based on a user-input matrix, finding the genes bound/regulated by a particular TF, and finding regulatory interactions between transcription factors. Enter a TF name to find the recommended matrix for a particular TF, or enter a nucleotide sequence to identify all TFs that could bind a particular region.

Proper citation: ScerTF (RRID:SCR_006121) Copy   

•   Source: SciCrunch Registry

https://github.com/bioinform/somaticseq

Software accurate somatic mutation detection pipeline implementing stochastic boosting algorithm to produce somatic mutation calls for both single nucleotide variants and small insertions and deletions. NGS variant calling and classification.

Proper citation: SomaticSeq (RRID:SCR_024891) Copy   

•   Source: SciCrunch Registry

https://github.com/xinhe-lab/GSFA

Software R package that performs sparse factor analysis and differential gene expression discovery simultaneously on single cell CRISPR screening data.

Proper citation: Guided Sparse Factor Analysis (RRID:SCR_025023) Copy   

•   Source: SciCrunch Registry

https://www.npatlas.org

Open access knowledge base for microbial natural products discovery. Database of microbially derived natural product structures. Provides coverage of bacterial and fungal natural products to visualize chemical diversity. Includes compounds and contains referenced data for structure, compound names, source organisms, isolation references, total syntheses, and instances of structural reassignment. Interactive web portal permits searching by structure, substructure, and physical properties. Provides mechanisms for visualizing natural products chemical space and dashboards for displaying author and discovery timeline data. Atlas has been developed under FAIR principles.

Proper citation: Natural Products Atlas (RRID:SCR_025107) 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://www.nitrc.org/projects/nusdast

A repository of schizophrenia neuroimaging data collected from over 450 individuals with schizophrenia, healthy controls and their respective siblings, most with 2-year longitudinal follow-up. The data include neuroimaging data, cognitive data, clinical data, and genetic data.

Proper citation: Northwestern University Schizophrenia Data and Software Tool (NUSDAST) (RRID:SCR_014153) Copy   

•   Source: SciCrunch Registry

http://zhanglab.ccmb.med.umich.edu/I-TASSER/

Web server as integrated platform for automated protein structure and function prediction. Used for protein 3D structure prediction. Resource for automated protein structure prediction and structure-based function annotation.

Proper citation: I-TASSER (RRID:SCR_014627) Copy   

•   Source: SciCrunch Registry

http://ophid.utoronto.ca/i2d

Database of known and predicted mammalian and eukaryotic protein-protein interactions, it is designed to be both a resource for the laboratory scientist to explore known and predicted protein-protein interactions, and to facilitate bioinformatics initiatives exploring protein interaction networks. It has been built by mapping high-throughput (HTP) data between species. Thus, until experimentally verified, these interactions should be considered predictions. It remains one of the most comprehensive sources of known and predicted eukaryotic PPI. It contains 490,600 Source Interactions, 370,002 Predicted Interactions, for a total of 846,116 interactions, and continues to expand as new protein-protein interaction data becomes available.

Proper citation: I2D (RRID:SCR_002957) Copy   

•   Source: SciCrunch Registry

http://diseasome.eu

A disease / disorder relationships explorer and a sample of a map-oriented scientific work. It uses the Human Disease Network dataset and allows intuitive knowledge discovery by mapping its complexity. The Human Disease Network (official) dataset, a poster of the data and related book (Biology - The digital era, ISBN: 978-2-271-06779-1) are available. This kind of data has a network-like organization, and relations between elements are at least as important as the elements themselves. More data could be integrated to this prototype and could eventually bring closer phenotype and genotype. Results should be visual, but also printable. Creating posters can enhance collaborative work. It facilitates discussion and sharing of ideas about the data. This website initiative is an invitation to think about the benefits of networks exploration but above all it tries to outline future designs of scientific information systems.

Proper citation: Diseasome (RRID:SCR_002792) Copy   

•   Source: SciCrunch Registry