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http://humanmetabolism.org/

A comprehensive biochemical knowledge-base on human metabolism, this community-driven, consensus metabolic reconstruction integrates metabolic information from five different resources: * Recon 1, a global human metabolic reconstruction (Duarte et al, PNAS, 104(6), 1777-1782, 2007) * EHMN, Edinburgh Human Metabolic Network (Hao et al., BMC Bioinformatics 11, 393, 2010) * HepatoNet1, a liver metabolic reconstruction (Gille et al., Molecular Systems Biology 6, 411, 2010), * Ac/FAO module, an acylcarnitine/fatty acid oxidation module (Sahoo et al., Molecular bioSystems 8, 2545-2558, 2012), * a human small intestinal enterocytes reconstruction (Sahoo and Thiele, submitted). Additionally, more than 370 transport and exchange reactions were added, based on a literature review. Recon 2 is fully semantically annotated (Le Nov��re, N. et al. Nat Biotechnol 23, 1509-1515, 2005) with references to persistent and publicly available chemical and gene databases, unambiguously identifying its components and increasing its applicability for third-party users. Here you can explore the content of the reconstruction by searching/browsing metabolites and reactions. Recon 2 predictive model is available in the Systems Biology Markup Language format.

Proper citation: Recon x (RRID:SCR_006345) Copy   

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http://cossmos.slu.edu/

Database to search through the nucleic acid structures from the Protein Data Bank and examine structural motifs, including (a)symmetric internal loops, bulge loops, and hairpin loops. They have compiled over 2,000 three-dimensional structures, which can now be searched using different parameters, including PDB information, experimental technique, sequence, and motif type. RNA secondary structure is important for designing therapeutics, understanding protein-RNA binding and predicting tertiary structure of RNA. Several databases and downloadable programs exist that specialize in the three-dimensional (3D) structure of RNA, but none focus specifically on secondary structural motifs such as internal, bulge and hairpin loops. To create the RNA CoSSMos database, 2156 Protein Data Bank (PDB) files were searched for internal, bulge and hairpin loops, and each loop''''s structural information, including sugar pucker, glycosidic linkage, hydrogen bonding patterns and stacking interactions, was included in the database. False positives were defined, identified and reclassified or omitted from the database to ensure the most accurate results possible. Users can search via general PDB information, experimental parameters, sequence and specific motif and by specific structural parameters in the subquery page after the initial search. Returned results for each search can be viewed individually or a complete set can be downloaded into a spreadsheet to allow for easy comparison. The RNA CoSSMos database is updated weekly.

Proper citation: RNA CoSSMos (RRID:SCR_006120) Copy   

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http://worfdb.dfci.harvard.edu/

Database that integrates and disseminates the data from the cloning of complete set of predicted protein-encoding ORFs of Caenorhabditis elegans. It also allows the community to search for availability and quality of cloned ORFs. So far, ORF sequence tags (OSTs) obtained for all individual clones have allowed exon structure corrections for ORFs originally predicted by the C. elegans sequencing consortium. The database contains this OST information along with data pertinent to the cloning process.

Proper citation: WorfDB (RRID:SCR_006028) Copy   

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http://www.wwpdb.org/

Public global Protein Data Bank archive of macromolecular structural data overseen by organizations that act as deposition, data processing and distribution centers for PDB data. Members are: RCSB PDB (USA), PDBe (Europe) and PDBj (Japan), and BMRB (USA). This site provides information about services provided by individual member organizations and about projects undertaken by wwPDB. Data available via websites of its member organizations.

Proper citation: Worldwide Protein Data Bank (wwPDB) (RRID:SCR_006555) Copy   

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http://murphylab.web.cmu.edu/services/SLIF/

SLIF finds fluorescence microscope images in on-line journal articles, and indexes them according to cell line, proteins visualized, and resolution. Images can be accessed via the SLIF Web database. SLIF takes on-line papers and scans them for figures that contain fluorescence microscope images (FMIs). Figures typically contain multiple FMIs, to SLIF must segment these images into individual FMIs. When the FMI images are extracted, annotations for the images (for instance, names of proteins and cell-lines) are also extracted from the accompanying caption text. Protein annotation are also used to link to external databases, such as the Gene Ontology DB. The more detailed process includes: segmentation of images into panels; panel classification, to find FMIs; segmentation of the caption, to find which portions of the caption apply to which panels; text-based entity extraction; matching of extracted entities to database entries; extraction of panel labels from text and figures; and alignment of the text segments to the panels. Extracted FMIs are processed to find subcellular location features (SLFs), and the resulting analyzed, annotated figures are stored in a database, which is accessible via SQL queries.

Proper citation: Subcellular Location Image Finder (RRID:SCR_006723) Copy   

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http://www.mbio.ncsu.edu/RNaseP/home.html

Ribonuclease P is responsible for the 5''-maturation of tRNA precursors. Ribonuclease P is a ribonucleoprotein, and in bacteria (and some Archaea) the RNA subunit alone is catalytically active in vitro, i.e. it is a ribozyme. The Ribonuclease P Database is a compilation of ribonuclease P sequences, sequence alignments, secondary structures, three-dimensional models and accessory information. The database contains information on bacterial, archaeal, and eukaryotic RNase P. The RNase P and protein sequences are available from phylogentically-arranged lists, individual sequences, or aligned in GenBank format. The database also provides secondary structures and 3D models, as well as movies, still images, and other accessory information.

Proper citation: RNase P Database (RRID:SCR_006680) Copy   

•   Source: SciCrunch Registry

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   

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https://github.com/vpc-ccg/svict

Software tool for detecting structural variations from cell free DNA containing low dilutions of circulating tumor DNA.

Proper citation: SViCT (RRID:SCR_023656) Copy   

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https://www.crisprscan.org/

Web tool for predictive sgRNA-scoring that captures sequence features affecting Cas9/sgRNA activity in vivo. Scoring algorithm to help select the best gRNAs for CRISPR.

Proper citation: CRISPRscan (RRID:SCR_023777) Copy   

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https://pathvisio.org/

Software visualization tool for biological pathways. Pathway analysis and drawing software which allows drawing, editing, and analyzing biological pathways. Developed in Java and can be extended with plugins.

Proper citation: PathVisio (RRID:SCR_023789) Copy   

•   Source: SciCrunch Registry

http://drugdesigndata.org

Project portal's database of protein-ligand data sets provided by pharmaceutical partners that provide atomic details of drug mechanisms that will be used to improve computer-aided drug-design methods and thus accelerate drug discovery. The project aims to help companies release the high-quality data they have generated, which has incredible value to researchers working to improve methods of computer-aided drug discovery. Everyone stands to benefit from the ability to develop new medications more quickly and inexpensively. What computational chemists globally are trying to do is to make faster, more accurate, more predictive programs to speed up the process. Part of their mission is to engage the community in these challenges to test newly developed predictive algorithms.

Proper citation: Drug Design Data Resource (RRID:SCR_000497) Copy   

•   Source: SciCrunch Registry

https://openmm.org/

Software toolkit to run modern molecular simulations. It can be used either as a standalone application for running simulations, or as a library that enables accelerated calculations for molecular dynamics on high-performance computer architectures.

Proper citation: OpenMM (RRID:SCR_000436) Copy   

•   Source: SciCrunch Registry

http://www.agbase.msstate.edu/

A curated, open-source, web-accessible resource for functional analysis of agricultural plant and animal gene products. Our long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase provides tools designed to assist with the analysis of proteomics data and tools to evaluate experimental datasets using the GO. Additional tools for sequence analysis are also provided. We use controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species. AgBase will also accept annotations from any interested party in the research communities. AgBase develops freely available tools for functional analysis, including tools for using GO. We appreciate any and all questions, comments, and suggestions. AgBase uses the NCBI Blast program for searches for similar sequences. And the Taxonomy Browser allows users to find the NCBI defined taxon ID for or taxon name for different organisms.

Proper citation: AgBase (RRID:SCR_007547) Copy   

•   Source: SciCrunch Registry

http://www.biocheminfo.org/klotho/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. A database of biochemical compound information. All files are available for download, and all entries are cataloged by accession number. Klotho is part of a larger attempt to model biological processes, beginning with biochemistry.

Proper citation: Klotho: Biochemical Compounds Declarative Database (RRID:SCR_007714) Copy   

•   Source: SciCrunch Registry

http://metallo.scripps.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 24, 2013. Database and Browser containing quantitative information on all the metal-containing sites available from structures in the PDB distribution. This database contains geometrical and molecular information that allows the classification and search of particular combinations of site characteristics, and answer questions such as: How many mononuclear zinc-containing sites are five coordinate with X-ray resolution better than 1.8 Angstroms?, and then be able to visualize and manipulate the matching sites. The database also includes enough information to answer questions involving type and number of ligands (e.g. "at least 2 His"), and include distance cutoff criteria (e.g. a metal-ligand distance no more than 3.0 Angstroms and no less than 2.2 Angstroms). This database is being developed as part of a project whose ultimate goal is metalloprotein design, allowing the interactive visualization of geometrical and functional information garnered from the MDB. The database is created by automatic recognition and extraction of metal-binding sites from metal-containing proteins. Quantitative information is extracted and organized into a searchable form, by iterating through all the entries in the latest PDB release (at the moment: September 2001). This is a comprehensive quantitative database, which exists in SQL format and contains information on about 5,500 proteins.

Proper citation: Metalloprotein Site Database (RRID:SCR_007780) Copy   

•   Source: SciCrunch Registry

http://www.chibi.ubc.ca/Gemma

Resource for reuse, sharing and meta-analysis of expression profiling data. Database and set of tools for meta analysis, reuse and sharing of genomics data. Targeted at analysis of gene expression profiles. Users can search, access and visualize coexpression and differential expression results.

Proper citation: Gemma (RRID:SCR_008007) Copy   

•   Source: SciCrunch Registry

http://integrativemodeling.org/

An open source C++ and Python toolbox for solving complex modeling problems, and a number of applications for tackling some common problems in a user-friendly way. Its broad goal is to contribute to a comprehensive structural characterization of biomolecules ranging in size and complexity from small peptides to large macromolecular assemblies, by integrating data from diverse biochemical and biophysical experiments. It can also be used from the Chimera molecular modeling system, or via one of several web applications.

Proper citation: Integrative Modeling Platform (RRID:SCR_002982) Copy   

•   Source: SciCrunch Registry

http://www.zfishbook.org/NGP/journalcontent/SCORE/SCORE.html

Narrative resource describing a visual data analysis and collection approach that takes advantage of the cylindrical nature of the zebrafish allowing for an efficient and effective method for image capture called, Specimen in a Corrected Optical Rotational Enclosure (SCORE) Imaging. To achieve a non-distorted image, zebrafish were placed in a fluorinated ethylene propylene (FEP) tube with a surrounding, optically corrected imaging solution: water. By similarly matching the refractive index of the housing (FEP tubing) to that of the inner liquid and outer liquid (water), distortion was markedly reduced, producing a crisp imagable specimen that is able to be fully rotated 360 degrees. A similar procedure was established for fixed zebrafish embryos using convenient, readily available borosilicate capillaries surrounded by 75% glycerol. The method described could be applied to chemical genetic screening and other, related high-throughput methods within the fish community and among other scientific fields.

Proper citation: Zebrafish - SCORE Imaging: Specimen in a Corrected Optical Rotational Enclosure (RRID:SCR_001300) Copy   

•   Source: SciCrunch Registry

http://publications.nigms.nih.gov/computinglife/

An NIGMS magazine that showcases the exciting ways that scientists are using the power of computers to expand our knowledge of biology and medicine. From text messaging friends to navigating city streets with GPS technology, we''re all living the computing life. But as we''ve upgraded from snail mail and compasses, so too have scientists. Computer advances now let researchers quickly search through DNA sequences to find gene variations that could lead to disease, simulate how flu might spread through your school and design three-dimensional animations of molecules that rival any video game. By teaming computers and biology, scientists can answer new and old questions that could offer insights into the fundamental processes that keep us alive and make us sick. This booklet introduces you to just some of the ways that physicists, biologists and even artists are computing life. Each section focuses on a different research problem, offers examples of current scientific projects and acquaints you with the people conducting the work. You can follow the links for online extras and other opportunities to learn aboutand get involved inthis exciting new interdisciplinary field.

Proper citation: NIGMS Computing Life (RRID:SCR_005850) Copy   

•   Source: SciCrunch Registry

http://www.fruitfly.org

Database on the sequence of the euchromatic genome of Drosophila melanogaster In addition to genomic sequencing, the BDGP is 1) producing gene disruptions using P element-mediated mutagenesis on a scale unprecedented in metazoans; 2) characterizing the sequence and expression of cDNAs; and 3) developing informatics tools that support the experimental process, identify features of DNA sequence, and allow us to present up-to-date information about the annotated sequence to the research community. Resources * Universal Proteomics Resource: Search for clones for expression and tissue culture * Materials: Request genomic or cDNA clones, library filters or fly stocks * Download Sequence data sets and annotations in fasta or xml format by http or ftp * Publications: Browse or download BDGP papers * Methods: BDGP laboratory protocols and vector maps * Analysis Tools: Search sequences for CRMs, promoters, splice sites, and gene predictions * Apollo: Genome annotation viewer and editor September 15, 2009 Illumina RNA-Seq data from 30 developmental time points of D. melanogaster has been submitted to the Short Read Archive at NCBI as part of the modENCODE project. The data set currently contains 2.2 billion single-end and paired reads and over 201 billion base pairs.

Proper citation: Berkeley Drosophila Genome Project (RRID:SCR_013094) Copy   

•   Source: SciCrunch Registry