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https://github.com/hms-dbmi/spp

R analysis and processing package for Illumina platform Chip-Seq data.

Proper citation: SPP (RRID:SCR_001790) Copy   

•   Source: SciCrunch Registry

http://mods.rna.albany.edu

The RNA modification database provides a comprehensive listing of posttranscriptionally modified nucleosides from RNA. Information provided for each nucleoside includes: the type of RNA in which it occurs and phylogenetic distribution; common chemical name and symbol; Chemical Abstracts registry number and index name; chemical structure; initial literature citations for structural characterization or occurrence, and for chemical synthesis. Both the structural diversity and extent of posttranscriptional modification in RNA is remarkable, with 107 different nucleosides presently known in all types of RNA. The discovery of new modified nucleosides as well as increasing knowledge of the array of functional roles of modification, based largely on extensive studies of tRNA, mandates a need for a comprehensive database of RNA nucleosides. The RNA Modification Database is maintained as an extension of the initial version published in mid-1994. The database consists of all RNA-derived ribonucleosides of known structure, including those from established sequence positions, as well as those detected or characterized from hydrolysates of RNA. The information provided permits access to the modified nucleoside literature through provision of both computer-searchable Chemical Abstracts registry numbers and key literature citations. This database also provides an historical record of the initial reports of occurrence, characterization and chemical synthesis of modified nucleosides from RNA. It is our judgement that the total number of RNA nucleosides listed, and the chemical structures reported, are very accurate. However, the distributions listed are in some cases a matter of concern, due primarily to the possibility of inhomogeneity of the RNA isolate and the use of methods of nucleoside identification that are not sufficiently rigorous. Reinvestigation of some of the unusual or single-report source distributions is warranted, and will likely lead to future refinements in the listings. The authors invite comments concerning new entries, errors or omissions and on the format presently used for electronic access to the database.

Proper citation: RNA Modification Database (RRID:SCR_003535) Copy   

•   Source: SciCrunch Registry

https://www.cgl.ucsf.edu/chimera/

Software tool for interactive visualization and analysis of molecular structures and related data, including density maps, supramolecular assemblies, sequence alignments, docking results, trajectories, and conformational ensembles. High-quality images and animations can be generated. Chimera includes complete documentation and several tutorials.

Proper citation: UCSF Chimera (RRID:SCR_004097) Copy   

•   Source: SciCrunch Registry

http://www.tcdb.org/

Curated, relational database containing sequence, classification, structural, functional and evolutionary information about transport systems from variety of living organisms based on IUBMB-approved transporter classification (TC) system. Descriptions, TC numbers, and examples of over 600 families of transport proteins are provided. TC system is analogous to Enzyme Commission (EC) system for classification of enzymes, except that it incorporates both functional and phylogenetic information. TCDB users may submit their own sequenced proteins and descriptions for inclusion into database. The software tools used are all freely available for download. These programs are used for analysis of Protein and DNA sequences. Programs require UNIX server to run.

Proper citation: Transporter Classification Database (RRID:SCR_004490) Copy   

•   Source: SciCrunch Registry

https://github.com/mwang87/MassQueryLanguage

Software application for universal searching of Mass Spectrometry data. Open source MS query language for flexible and mass spectrometer manufacturer-independent mining of MS data. Implements common MS terminology to build consensus vocabulary to search for MS patterns in single mass spectrometry run. Enables set of mass spectrometry patterns to be queried directly from raw data.

Proper citation: MassQL (RRID:SCR_025106) Copy   

•   Source: SciCrunch Registry

https://github.com/bmvdgeijn/WASP/

Software allele-specific pipeline for unbiased read mapping and molecular QTL discovery. Allele-specific software for robust molecular quantitative trait locus discovery.

Proper citation: WASP (RRID:SCR_025497) Copy   

•   Source: SciCrunch Registry

https://bioxtas-raw.readthedocs.io/en/latest/

Software tool as GUI based Python program for reduction and analysis of small-angle X-ray solution scattering (SAXS) data.Small-angle scattering data reduction and analysis. Available on Windows, macOS (and OS X), and Linux.

Proper citation: BioXTAS RAW (RRID:SCR_025769) Copy   

•   Source: SciCrunch Registry

https://biochem.missouri.edu/chapman/software.htm

Software for fitting of atomic models into density maps derived from x-ray crystallography or electron microscopy.

Proper citation: RSRef (RRID:SCR_017211) Copy   

•   Source: SciCrunch Registry

https://www.phenix-online.org/documentation/reference/refinement.html

Software tool for a general purpose crystallographic structure refinement within the PHENIX package. Serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB.

Proper citation: Phenix.refine (RRID:SCR_016736) Copy   

•   Source: SciCrunch Registry

https://github.com/brentp/mosdepth

Software command line tool for rapidly calculating genome wide sequencing coverage. Measures depth from BAM or CRAM files at either each nucleotide position in genome or for sets of genomic regions. Used for fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing quick coverage calculation for genomes and exomes.

Proper citation: mosdepth (RRID:SCR_018929) Copy   

•   Source: SciCrunch Registry

http://code.google.com/p/lapdftext/

Software that facilitates accurate extraction of text from PDF files of research articles for use in text mining applications. It is intended for both scientists and natural language processing (NLP) engineers interested in getting access to text within specific sections of research articles. The system extracts text blocks from PDF-formatted full-text research articles and classifies them into logical units based on rules that characterize specific sections. The LA-PDFText system focuses only on the textual content of the research articles. The current version of LA-PDFText is a baseline system that extracts text using a three-stage process: * identification of blocks of contiguous text * classification of these blocks into rhetorical categories * extraction of the text from blocks grouped section-wise.

Proper citation: lapdftext (RRID:SCR_006167) Copy   

•   Source: SciCrunch Registry

http://www.sci.utah.edu/cibc/software/231-biomesh3d.html

A free, easy to use program for generating quality meshes for use in biological simulations. It is currently integrated with SCIRun and uses the SCIRun system to visualize the intermediate results. The BioMesh3D program uses a particle system to distribute nodes on the separating surfaces that separate the different materials and then uses the TetGen software package to generate a full tetrahedral mesh.

Proper citation: BioMesh3D (RRID:SCR_009534) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/X2K/

Software tool to produce inferred networks of transcription factors, proteins, and kinases predicted to regulate the expression of the inputted gene list by combining transcription factor enrichment analysis, protein-protein interaction network expansion, with kinase enrichment analysis. It provides the results as tables and interactive vector graphic figures.

Proper citation: eXpression2Kinases (RRID:SCR_016307) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3149502/

Software for comprehensive quantitative measure of splicing impact of complete set of RNA 6-mer sequences by deep sequencing successfully spliced transcripts.

Proper citation: ESRseq score (RRID:SCR_022270) Copy   

•   Source: SciCrunch Registry

https://faculty.chemistry.harvard.edu/shakhnovich/software/coarse-grained-co-translational-folding-analysis

Software for statistical approach to identify loci within genes that are both significantly enriched in slowly translated codons and evolutionarily conserved, and also co-translational protein folding model.

Proper citation: Coarse grained co-translational folding analysis (RRID:SCR_022271) Copy   

•   Source: SciCrunch Registry

http://panomics.pnnl.gov/

Biomedical technology research center that develops and integrates new proteomic technologies for collaborative and service studies, disseminating the new technologies and training scientists in their use.

Proper citation: Proteomics Research Center for Integrative Biology (RRID:SCR_001098) Copy   

•   Source: SciCrunch Registry

https://ncxt.org/

Biomedical technology research center that develops novel cellular imaging technologies, specifically soft X-ray tomography, for visualizing and quantifying the internal structure of whole, hydrated cells, and high-numerical aperture fluorescence microscopy for locating the position of specific cellular molecules. Data from these two imaging modalities can be combined to form a single, correlated imaging view of a cell.

Proper citation: National Center for X-ray Tomography (RRID:SCR_001433) Copy   

•   Source: SciCrunch Registry

http://www.nbcr.net/

Biomedical technology research center that conducts, catalyzes and enables multiscale biomedical research, focusing on four key activities: 1) integrating computational, data and visualization resources in a transparent, advanced grid environment to enable better access to distributed data, computational resources, instruments and people; 2) developing and deploying advanced computational tools for modeling and simulation, data analysis, query and integration, three-dimensional image processing and interactive visualization; 3) delivering and supporting advanced grid/cyberinfrastructure for biomedical researchers; and 4) training a cadre of new researchers to have an interdisciplinary, working knowledge of computational technology relevant to biomedical scientists. NBCR enables biomedical scientists to address the challenge of integrating detailed structural measurements from diverse scales of biological organization that range from molecules to organ systems in order to gain quantitative understanding of biological function and phenotypes. Predictive multi-scale models and their driving biological research problems together address issues in modeling of sub-cellular biophysics, building molecular modeling tools to accelerate discovery, and defining tools for patient-specific multi-scale modeling. NBCR furthers these driving problems by developing tools and models based on rapid advances in mathematics and information technology, incorporating them into NBCR pipelines or problem solving environments, and addressing the inevitable changes in the underlying cyber-infrastructure technologies and continually adapting codes over time. Their technology focus integrates both the biological applications and the underlying support software into reproducible science workflows that can function across a number of physical infrastructures.

Proper citation: National Biomedical Computation Resource (RRID:SCR_002656) Copy   

•   Source: SciCrunch Registry

http://ncmir.ucsd.edu/

Biomedical technology research center that develops computer-aided, advanced microscopy for the acquisition of structural and functional data in the dimensional range of 1 nm to 100 um, a range encompassing macromolecules, subcellular structures and cells. Novel specimen-staining methods, imaging instrumentsincluding intermediate high-voltage transmission electron microscopes (IVEMs) and high-speed, large-format laser-scanning light microscopesand computational capabilities are available for addressing mesoscale biological microscopy of proteins and macromolecular complexes in their cellular and tissue environments. These technologies are developed to bridge understanding of biological systems between the gross anatomical and molecular scales and to make these technologies broadly available to biomedical researchers. NCMIR provides expertise, infrastructure, technological development, and an environment in which new information about the 3D ultrastructure of tissues, cells, and macromolecular complexes may be accurately and easily obtained and analyzed. NCMIR fulfills its mission through technology development, collaboration, service, training, and dissemination. It aims to develop preparative methods and analytical approaches to 3D microscopy applicable to neurobiology and cell biology, incorporating equipment and implementing software that expand the analysis of 3D structure. The core research activities in the areas of specimen development, instrument development, and software infrastructures maximize the advantages of higher voltage electron microscopy and correlated light microscopies to make ambitious imaging studies across scales routine, and to facilitate the use of resources by biomedical researchers. NCMIR actively recruits outside users who will not only make use of these resources, but who also will drive technology development and receive training.

Proper citation: National Center for Microscopy and Imaging Research (RRID:SCR_002655) Copy   

•   Source: SciCrunch Registry

http://www.mc.vanderbilt.edu/root/vumc.php?site=ims

Biomedical technology research center that advances the technology of Imaging Mass Spectrometry, facilitates the application of this novel imaging modality to problems of biological and clinical significance, and promotes the adoption of these technologies by a larger community of scientists and clinicians. Technical innovations include next-generation hardware, software and methods. Technology development is conducted by an interdisciplinary team of scientists and engineers, both within the Resource and through collaborative relationships with other universities, research institutes, and private industry. Development milestones are guided by Driving Biological Projects that require specific advancements in Imaging Mass Spectrometry in order to address biological problems. By working together, they anticipate new insights into these biological systems and a better understanding of health and disease at the molecular level that translates to improved patient care. The training mission of the Resource is accomplished through a variety of educational programs where Resource scientists and collaborators share their knowledge and experience with those interested in learning more about the technology.

Proper citation: VU National Research Resource for Imaging Mass Spectrometry (RRID:SCR_006904) Copy   

•   Source: SciCrunch Registry