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https://github.com/yarden/MISO/blob/fastmiso/docs/source/sashimi.rst
Software tool for quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions.
Proper citation: Sashimiplot (RRID:SCR_016861) Copy
http://www.cs.cmu.edu/~jernst/stem/
The Short Time-series Expression Miner (STEM) is a Java program for clustering, comparing, and visualizing short time series gene expression data from microarray experiments (~8 time points or fewer). STEM allows researchers to identify significant temporal expression profiles and the genes associated with these profiles and to compare the behavior of these genes across multiple conditions. STEM is fully integrated with the Gene Ontology (GO) database supporting GO category gene enrichment analyses for sets of genes having the same temporal expression pattern. STEM also supports the ability to easily determine and visualize the behavior of genes belonging to a given GO category or user defined gene set, identifying which temporal expression profiles were enriched for these genes. (Note: While STEM is designed primarily to analyze data from short time course experiments it can be used to analyze data from any small set of experiments which can naturally be ordered sequentially including dose response experiments.) Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: Short Time-series Expression Miner (STEM) (RRID:SCR_005016) Copy
An open-source general packing algorithm that packs 3D objects onto surfaces, into volumes, and around volumes. It provides a general architecture to allow various packing algorithms to interoperate efficiently in the same model. autoPack can incorporate any packing solution into its modular python program architecture, but is currently optimized to provide a novel solution to the loose packing problem which places objects of discrete size into place (compared to advancing front, popcorn, or other fast tight-packing solutions that allow objects to scale to arbitrary masses.) Most popular 3D software programs now contain robust physics engines based on Bullet that can separate small collections of overlapping objects or allow volumes to be filled by pouring shapes from generators, but these approaches fails for large complex systems and result in either overlapping geometry, crashed software, or non-random gradients. Most packing algorithms are designed to position objects as efficiently as possible, but autoPack allows the user to select from random loose packing to highly organized packing methods����??even to choose both methods at the same time. autoPack positions 3D geometries into, onto, and around volumes with minimal to zero overlap. autoPack mixes several packing approaches and procedural growth algorithms. autoPack can thus place objects with forces and constraints to allow a high degree of control ranging from completely random distributions to highly ordered structures. * zero to minimal overlaps depending on the method used * accuracy vs speed parameters selected by the user * zero edge effects * complete control, from fully random to fully ordered distributions * agent-based interaction, weighting, and collision control
Proper citation: Autopack (RRID:SCR_006830) Copy
https://github.com/CBL-ORION/orion
Project to develop tools that explore single neuron function via sophisticated image analysis. ORION software bridges advanced optical imaging and compartmental modeling of neuronal function by rapidly, accurately, and robustly generating, from structural image data, a cylindrical morphology model suitable for simulating neuronal function.
Proper citation: ORION (RRID:SCR_010621) Copy
http://bioinformatics.clemson.edu/G-SESAME/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 2,2025. G-SESAME contains a set of tools. They include: tools for measuring the semantic similarity of GO terms; tools for measuring the functional similarity of genes; and tools for clustering genes based on their GO term annotation information. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: G-SESAME - Gene Semantic Similarity Analysis and Measurement Tools (RRID:SCR_005816) Copy
DOMMINO is a comprehensive structural database on macromolecular interactions. As of June, 2011, it contains more than 407,000 binary interactions. The distinctive features of DOMMINO are: # Automated updates: DOMMINO is fully automated and is designed to update itself on a weekly basis, one day after a PDB weekly update. Thus, the community will be able to study macromolecular interactions almost immediately after they are released by PDB. # Coverage of non-domain mediated interactions: In addition to domain-domain and domain-peptide interactions the database characterizes the interaction between domains and unstructured protein regions that are not parts of a domain, such as inter-domain linkers and N- and C-termini. The interactions that involve the latter unstructured parts of proteins have been included to the database for the first time providing additional ~186,000 interactions (~45% of the total number of interactions, as of June, 2011). # Coverage of new structural domains: DOMMINO employs one of the most accurate structural classifications of proteins, SCOP. In addition to the existing SCOP-annotated domains, we employ a state-of-the-art machine learning approach to classify newer protein structures into existing SCOP families. With the progress of structural genomics, we do not expect a significant growth of the number of structurally novel folds or protein families and therefore our method allows covering almost all new protein structures. In total, using this predictive approach has allowed us to add more than 261,000 new interactions, almost twice as many as existing SCOP-annotated interactions. # The web-interface is designed to give the user a possibility of a flexible search as well as the capability to study macromolecular interactions in a PDB structure at the interaction network level and at the individual interface level. The web interface of the DOMMINO database includes a comprehensive list of help topics linked to the specific actions. In addition, we have designed a step-by-step tutorial that covers all aspects of working with the data from DOMMINO using the web interface.
Proper citation: DOMMINO - Database Of MacroMolecular INteractiOns (RRID:SCR_005958) Copy
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
http://www.broadinstitute.org/mammals/haploreg/haploreg.php
HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.
Proper citation: HaploReg (RRID:SCR_006796) Copy
http://www.mbl.org/mbl_main/atlas.html
High-resolution electronic atlases for mouse strains c57bl/6j, a/j, and dba/2j in either coronal or horizontal section. About this Atlas: The anterior-posterior coordinates are taken from an excellent print atlas of a C57BL/6J brain by K. Franklin and G. Paxinos (The Mouse Brain in Stereotaxic Coordinates, Academic Press, San Diego, 1997, ISBN Number 0-12-26607-6; Library of Congress: QL937.F72). The abbreviations we have used to label the sections conform to those in the Franklin-Paxinos atlas. A C57BL/6J mouse brain may contain as many as 75 million neurons, 23 million glial cells, 7 million endothelial cells associated with blood vessels, and 3 to 4 million miscellaneous pial, ependymal, and choroid plexus cells (see data analysis in Williams, 2000). We have not yet counted total cell number in DBA/2J mice, but the counts are probably appreciably lower.The brain and sections were all processed as described in our methods section. The enlarged images have a pixel count of 1865 x 1400 and the resolution is 4.5 microns/pixel for the processed sections.Plans: In the next several years we hope to add several additional atlases of the same sort for other strains of mice. A horizontal C57BL/6J atlas and a DBA/2J coronal atlas were completed by Tony Capra, summer 2000, and additional atlases may be made over the next several years. As describe in the MBL Procedures Section is not hard to make your own strain-specific atlas from the high resolution images in the MBL.
Proper citation: Mouse Brain Atlases (RRID:SCR_007127) Copy
http://www.cpc.unc.edu/projects/addhealth
Longitudinal study of a nationally representative sample of adolescents in grades 7-12 in the United States during the 1994-95 school year. Public data on about 21,000 people first surveyed in 1994 are available on the first phases of the study, as well as study design specifications. It also includes some parent and biomarker data. The Add Health cohort has been followed into young adulthood with four in-home interviews, the most recent in 2008, when the sample was aged 24-32. Add Health combines longitudinal survey data on respondents social, economic, psychological and physical well-being with contextual data on the family, neighborhood, community, school, friendships, peer groups, and romantic relationships, providing unique opportunities to study how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. The fourth wave of interviews expanded the collection of biological data in Add Health to understand the social, behavioral, and biological linkages in health trajectories as the Add Health cohort ages through adulthood. The restricted-use contract includes four hours of free consultation with appropriate staff; after that, there''s a fee for help. Researchers can also share information through a listserv devoted to the database.
Proper citation: Add Health (National Longitudinal Study of Adolescent Health) (RRID:SCR_007434) Copy
http://posa.sanfordburnham.org/fatcat-cgi/cgi/FSN/fsn.pl
Flexible Structural Neighborhood is a database of structural neighbors of proteins as seen by FATCAT - a flexible protein structure alignment program. The server accepts either a protein (PDB ID) or a domain (SCOP ID) as a query. For the former case, the server first displays the information of chains and domains of a given protein. Afterwards, users can retrieve similar structures for a domain (if domain information is available, i.e., the protein is collected by SCOP), or for a chain otherwise. The protein structure database we collected for similar structure search includes a representative set at 90% sequence identity of SCOP domains, and of up-to-date PDB entries that are not included in the latest release of SCOP.
Proper citation: FATCAT Flexible Structural Neighborhood (RRID:SCR_007665) Copy
http://www.scienceexchange.com/facilities/vcu-nanomaterials-characterization-center-vcu
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 15,2024. Nanomaterials Characterization Center at Virginia Commonwealth University is a state of the art 4000 sq. ft. facility located within the new Health and Life Science Engineering Facility. The Center provides an academic structure for students in natural sciences, mathematics, engineering, and medicine to participate in nanoscience and nanotechnology research to acquire the skills necessary to pursue such careers. In the past year, VCU received two National Science Foundation major research instrumentation grants totaling more than $1.6 million to expand its capabilities for research in materials science. Combining these federal awards with state instrumentation grants and private donations, the facility has been able to build a state of the art facility with over $5 million in new equipment. This new equipment will allow faculty and student researchers from both VCU campuses, as well as other universities.
Proper citation: VCU Nanomaterials Characterization Center (RRID:SCR_012162) Copy
https://www.ezbiocloud.net/tools/orthoaniu
Software tool for calculating average nucleotide identity.
Proper citation: OrthoANIu (RRID:SCR_022562) Copy
https://github.com/raphael-group/chisel
Software tool to infer allele and haplotype specific copy numbers in individual cells from low coverage single cell DNA sequencing data. Integrates weak allelic signals across individual cells, powering strength of single cell sequencing technologies to overcome weakness. Includes global clustering of RDRs and BAFs, and rigorous model selection procedure for inferring genome ploidy that improves both inference of allele specific and total copy numbers.
Proper citation: CHISEL (RRID:SCR_023220) Copy
https://github.com/mhammell-laboratory/TEtranscripts
Software package for including transposable elements in differential enrichment analysis of sequencing datasets. Used for including transposable elements in differential expression analysis of RNA-seq datasets. RNAseq TE quantification tool.
Proper citation: TEtranscripts (RRID:SCR_023208) Copy
https://benjjneb.github.io/dada2/
Open source software R package for modeling and correcting Illumina sequenced amplicon errors. Fast and accurate sample inference from amplicon data with single nucleotide resolution.
Proper citation: DADA2 (RRID:SCR_023519) Copy
http://anya.igsb.anl.gov/Geneways/GeneWays.html
System for automatically extracting, analzying, visualizing and integrating molecular pathway data from the research literature. System focuses on interactions between molecular substances and actions, providing a graphical consensus view on the collected information. GeneWays is designed as open platform, allowing researchers to query, review and critique integrated information.
Proper citation: GeneWays (RRID:SCR_000572) Copy
http://www.marine-geo.org/portals/antarctic/
Accepts and provides access to geoscience data, primarily marine, collected from oceanographic expeditions in the Antarctic region. The synthesis began in 2003 as the Antarctic Multibeam Bathymetry and Geophysical Data Synthesis (AMBS) with a focus on multibeam bathymetry field data and other geophysical data from the Southern Ocean collected with the R/V N. B. Palmer. In 2005, the effort was expanded to include all routine underway geophysical and oceanographic data collected with both the R/V N. B. Palmer and R/V L. Gould, the two primary research vessels serving the US Antarctic Program. Data available include seafloor bathymetry, subbottom profiling, trackline gravity and magnetics, meteorological, and water column data as well as basic cruise information for all Palmer and Gould expeditions. Seafloor bathymetry data are provided both as raw swath data as well as in gridded form through the Global Multi-Resolution Topography (GMRT) synthesis. This gridded compilation of seafloor bathymetry data can be accessed through GeoMapApp, Create Maps and Grids and through an OGC-compliant Web Map Service. GeoMapApp is an integrated mapping application that provides access to many additional regional bathymetric grids, seismic, radar, gravity and magnetics profiles as well as other map and grid compilations for the Antarctic continent including LIMA.
Proper citation: Antarctic and Southern Ocean Data Portal (RRID:SCR_002193) Copy
http://biodev.ece.ucsb.edu/projects/bisquik/wiki
A scalable web-based system for biological image analysis, management and exploration. The Bisque system incorporates many features useful to imaging researchers from image capture to extensible image analysis and querying. At the core, bisque maintains a flexible database of images and experimental metadata. Image analyses can be incorporated into the system and deployed on clusters and desktops. Search and comparison of datasets by image data and content is supported. Novel semantic analyses are integrated into the system allowing high level semantic queries and comparison of image content. New features and testing of Bisque version: 0.5.1, among many others are: # Parallel execution of datasets # Rich interfaces for autogenerated module UI # Abstracted storage system for local, irods, etc.. They are using Mercurial for their source control system. This should be installed before proceeding. Browse source on-line, http://biodev.ece.ucsb.edu/projects/bisquik/browser Bisque Installation, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/InstallationInstructions05 Bisque DOWNLOAD, http://biodev.ece.ucsb.edu/projects/bisquik/wiki/download, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Bisque (RRID:SCR_005564) Copy
http://psidonline.isr.umich.edu/
Long-term longitudinal dataset with information on generational links and socioeconomic and health conditions of individuals over time. The central foci of the data are economic and demographic, with substantial detail on income sources and amounts, wealth, savings, employment, pensions, family composition changes, childbirth and marriage histories, and residential location. Over the life of the PSID, the NIA has funded supplements on wealth, health, parental health and long term care, housing, and the financial impact of illness, thus also making it possible to model retirement and residential mobility. Starting in 1999, much greater detail on specific health conditions and health care expenses is included for respondent and spouse. Other enhancements have included a question series about emotional distress (2001); the two stem questions from the Composite International Diagnostic Interview to assess symptoms of major depression (2003); a supplement on philanthropic giving and volunteering (2001-03); a question series on Internet and computer use (2003); linkage to the National Death Index with cause of death information for more than 4,000 individuals through the 1997 wave, updated for each subsequent wave; social and family history variables and GIS-linked environmental data; basic data on pension plans; event history calendar methodology to facilitate recall of employment spells (2001). The reporting unit is the family: single person living alone or sharing a household with other non-relatives; group of people related by blood, marriage, or adoption; unmarried couple living together in what appears to be a fairly permanent arrangement. Interviews were conducted annually from 1968 through 1997; biennial interviewing began in 1999. There is an oversample of Blacks (30%). Waves 1990 through 1995 included a 20% Hispanic oversample; within the Hispanic oversample, Cubans and Puerto Ricans were oversampled relative to Mexicans. All data from 1994 through 2001 are available as public release files; prior waves can be obtained in archive versions. The special files with weights for families are also available. Restricted files include the Geocode Match File with information for 1968 through 2001, the 1968-2001 Death File, and the 1991 Medicare Claims File. * Dates of Study: 1968-2003 * Study Features: Longitudinal, Minority Oversampling * Sample Size: 65,000+ Links * ICPSR Series: http://www.icpsr.umich.edu/icpsrweb/ICPSR/series/00131 * ICPSR 1968-1999: Annual Core Data: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/07439 * ICPSR 1968-1999: Supplemental Files: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03202 * ICPSR 1989-1990: Latino Sample: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/03203
Proper citation: Panel Study of Income Dynamics (RRID:SCR_008976) Copy
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