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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/
D2R Server is a tool for publishing relational databases on the Semantic Web. It enables RDF and HTML browsers to navigate the content of the database, and allows applications to query the database using the SPARQL query language. Data on the Semantic Web is modeled and represented in RDF. D2R Server uses a customizable D2RQ mapping to map database content into this format, and allows the RDF data to be browsed and searched the two main access paradigms to the Semantic Web. D2R Server''s Linked Data interface makes RDF descriptions of individual resources available over the HTTP protocol. An RDF description can be retrieved simply by accessing the resource''s URI over the Web. Using a Semantic Web browser like Tabulator (slides) or Disco, you can follow links from one resource to the next, surfing the Web of Data. The SPARQL interface enables applications to search and query the database using the SPARQL query language over the SPARQL protocol. Requests from the Web are rewritten into SQL queries via the mapping. This on-the-fly translation allows publishing of RDF from large live databases and eliminates the need for replicating the data into a dedicated RDF triple store. The latest source code is available from the project''s CVS repository and can be browsed online.
Proper citation: D2R Server - Publishing Relational Databases on the Semantic Web (RRID:SCR_004963) Copy
http://alchemy.sourceforge.net/
ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes. ALCHEMY is a method for automated calling of diploid genotypes from raw intensity data produced by various high-throughput multiplexed SNP genotyping methods. It has been developed for and tested on Affymetrix GeneChip Arrays, Illumina GoldenGate, and Illumina Infinium based assays. Primary motivations for ALCHEMY''s development was the lack of available genotype calling methods which can perform well in the absence of heterozygous samples (due to panels of inbred lines being genotyped) or provide accurate calls with small sample batches. ALCHEMY differs from other genotype calling methods in that genotype inference is based on a parametric Bayesian model of the raw intensity data rather than a generalized clustering approach and the model incorporates population genetic principles such as Hardy-Weinberg equilibrium adjusted for inbreeding levels. ALCHEMY can simultaneously estimate individual sample inbreeding coefficients from the data and use them to improve statistical inference of diploid genotypes at individual SNPs. The main documentation for ALCHEMY is maintained on the sourceforge-hosted MediaWiki system. Features * Population genetic model based SNP genotype calling * Simultaneous estimation of per-sample inbreeding coefficients, allele frequencies, and genotypes * Bayesian model provides posterior probabilities of genotype correctness as quality measures * Growing number of scripts and supporting programs for validation of genotypes against control data and output reformating needs * Multithreaded program for parallel execution on multi-CPU/core systems * Non-clustering based methods can handle small sample sets for empirical optimization of sample preparation techniques and accurate calling of SNPs missing genotype classes ALCHEMY is written in C and developed on the GNU/Linux platform. It should compile on any current GNU/Linux distribution with the development packages for the GNU Scientific Library (gsl) and other development packages for standard system libraries. It may also compile and run on Mac OS X if gsl is installed.
Proper citation: ALCHEMY (RRID:SCR_005761) Copy
Integrated framework for accessing grid resources that supports scientific exploration, workflow capture and replay, and a dynamic services oriented architecture. This framework provides researchers in the molecular sciences with a tool to discover remote grid application services and compose them as appropriate to the chemical and physical nature of the problem at hand. The initial set of application services include molecular quantum and classical chemistries (GAMESS, APBS, Polyrate), along with supporting services for visualization (QMView), databases, auxillary chemistry services, and documentation and education materials. * Rich-client Desktop Interface - Gemstone is a Firefox extension that provides a dynamic user interface to backend computational, data and visualization services. * Workflow Integration - Gemstone supports a workflow component based on Informnet (see http://grid-devel.sdsc.edu/informnet). They are adapting the Informnet workflow engine to support workflow publication and discovery, brokering, and fault tolerance. They are also adding support for automatic generation of workflows based on user interaction. * Strongy Typed Data Schemas - They are working extensively with CML, integrating their data schemas into workflow systems and providing bridges to the GamesXML that they defined.
Proper citation: Grid Enabled Molecular Science Through Online Networked Environments (RRID:SCR_008629) Copy
http://bc02.iis.sinica.edu.tw/gobu/manual/index.html
Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy
http://owlapi.sourceforge.net/
The OWL API is a Java API and reference implementation for creating, manipulating and serializing OWL Ontologies. The latest version of the API is focused towards OWL 2. The OWLAPI underpins ontology browsing and editing tools and platforms such as SWOOP and Protege4. Note that this API, or any other OWL-based API, can be used without an integrated OWL parser if you download a pre-converted OWL file generated from OBO. See OBO Ontologies List for all OBO ontologies converted to OWL (we do not list the full complement of OWL-based APIs here, only those of direct relevance to GO). The OWL API includes the following components: * An API for OWL 2 and an efficient in-memory reference implementation * RDF/XML parser and writer * OWL/XML parser and writer * OWL Functional Syntax parser and writer * Turtle parser and writer * KRSS parser * OBO Flat file format parser * Reasoner interfaces for working with reasoners such as FaCT++, HermiT, Pellet and Racer Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: OWL API (RRID:SCR_005734) Copy
http://neurofitter.sourceforge.net
Neurofitter is software for parameter tuning of electrophysiological neuron models. It automatically searches for sets of parameters of neuron models that best fit available experimental data, and therefore acts as an interface between neuron simulators, like Neuron or Genesis, and optimization algorithms, like Particle Swarm Optimization, Evolutionary Strategies, etc.
Proper citation: Neurofitter (RRID:SCR_005843) Copy
OrChem is an extension for the Oracle 11G database that adds registration and indexing of chemical structures to support fast substructure and similarity searching. The cheminformatics functionality is provided by the Chemistry Development Kit. OrChem provides similarity searching with response times in the order of seconds for databases with millions of compounds, depending on a given similarity cut-off. For substructure searching, it can make use of multiple processor cores on today''s powerful database servers to provide fast response times in equally large data sets. OrChem is an Oracle chemistry plug-in using the Chemistry Development Kit (CDK). The CDK is an open source Java library for Chemoinformatics and Bioinformatics. OrChem is maintained by the chemoinformatics and metabolism team of the European Bioinformatics Institute. Oracle Data cartridges extend the capabilities of the Oracle server. For chemistry various commercial cartridges exist that facilitate searching and analyzing chemical data. OrChem also provides functionality like this, but is not a cartridge. It doesn''t need Oracle''s extensibility architecture because its Java components run as Java stored procedures inside the Oracle standard JVM (Aurora). OrChem is suitable for Oracle 11G and onwards. Starting with Oracle 11g release 1 (11.1) there is a just-in-time(JIT) compiler for Oracle JVM environment. A JIT compiler for Oracle JVM enables much faster execution because it manages the invalidation, recompilation, and storage of code without an external mechanism. This new Oracle feature makes Java classes perform better than before.
Proper citation: OrChem (RRID:SCR_008865) Copy
http://sccn.ucsd.edu/wiki/BCILAB
Open Source MATLAB toolbox and EEGLAB plugin for the design, prototyping, testing, experimentation with, and evaluation of Brain-Computer Interfaces (BCIs), and other systems in the same computational framework. It facilitates the design and development of new methods for cognitive state estimation and their use in both offline data analysis and real-time applications. BCILAB includes an easily extensible collection of currently over 100 methods from the literature (covering signal processing, machine learning and BCI-specific methods). Aside from supporting advanced BCI research, a special aim of BCILAB is to facilitate the adoption of machine learning and advanced statistical modeling for functional neuroimaging purposes in tandem with the EEGLAB platform. The toolbox offers multiple different interfaces which link to the same backend functionality, including a GUI, scripting support (MATLAB-based), APIs for real-time processing, and a variety of extension component interfaces. MATLAB programming is not strictly necessary, as most BCILAB features can be accessed from the GUI, although it is required for batch scripting and custom extensions. The strength of MATLAB-based software lies in its resources for leading-edge scientific computing, as well as in the good support for rapid prototyping, but BCI systems developed in it can be used for real-time out-of-lab experimentation, and can in principle be deployed without the need for a MATLAB license. However, due to the complexity and overhead of the MATLAB environment, the system is best used as a research platform, and not as a product development environment -- end-user software is ideally re-implemented in a compiled language, after a suitable approach has been identified and extensively tested. The process of identifying and testing an approach involves more than just computation, but also data exploration and investigation - an area which is helped by the deep integration with the EEGLAB platform. In the future, this integration will be further strengthened, bringing rich statistical learning and signal processing into routine EEG analysis workflows. The toolbox has been developed by C. Kothe at the Swartz Center, inspired by the preceding PhyPA BCI toolbox created by C. Kothe and T. Zander at the Chair for Human-Machine Systems, Berlin Institute of Technology.
Proper citation: BCILAB (RRID:SCR_007013) Copy
https://github.com/Illumina/strelka/
Software for somatic single nucleotide variant (SNV) and small indel detection from sequencing data of matched tumor-normal samples. Strelka2 germline and somatic small variant caller.
Proper citation: Strelka2 (RRID:SCR_005109) Copy
https://github.com/2019surbhi/tinglab_ureter_analysis/tree/v1
Analysis code relevant to scRNA sequencing analysis. Code for Fink and Sona et.al. (2022) publication.
Proper citation: tinglab ureter analysis (RRID:SCR_022525) Copy
https://bioconductor.org/packages/FlowSorted.Blood.EPIC/
Software package includes new cell reference for adult peripheral blood deconvolution arrayed using Illumina HumanMethylationEPIC.Optimized library for reference based deconvolution of whole blood biospecimens assayed using Illumina HumanMethylationEPIC BeadArray.
Proper citation: FlowSorted.Blood.EPIC (RRID:SCR_022540) Copy
https://github.com/AlgoLab/CouGaR-g
Source code for "Accurate and Fast Clade Assignment via Deep Learning and Frequency Chaos Game Representation".
Proper citation: CouGaR-g (RRID:SCR_022952) Copy
https://github.com/shooshtarilab/Subsemble_Cell_Type_Classifier
Supervised ensemble machine learning classifier. Classification performance benchmark scripts.
Proper citation: Subsemble Cell Type Classifier (RRID:SCR_022784) Copy
https://github.com/protofilamentdude/Protofilament-Bending-Models
Code is written to be run with Matlab version r2020b or higher. Model accepts wave assay pulse amplitude data, and simultaneously solves and fits protofilament deflection models to deduce fundamental biophysical properties of microtubule protofilaments.
Proper citation: Protofilament Bending Models (RRID:SCR_023062) Copy
https://github.com/caraweisman/abSENSE
Software to interpret undetected homolog.Method that calculates probability that homolog of given gene would fail to be detected by homology search in given species, even if homolog were present and evolving normally.
Proper citation: abSENSE (RRID:SCR_023223) Copy
https://github.com/compbiolabucf/PTNet
Graph based learning model for protein expression estimation by considering miRNA-mRNA interactions. Estimates protein levels by considering miRNA-mRNA interaction network, mRNA expression and miRNA expression.
Proper citation: PTNet (RRID:SCR_022975) Copy
https://github.com/DeNardoLab/BehaviorDEPOT
Software tool for automated behavioral detection based on markerless pose tracking. Behavioral analysis tool to first compile and clean point-tracking output from DeepLabCut, and then classify behavioral epochs using custom behavior classifiers. Used to detect frame by frame behavior from video time series and can analyze results of common experimental assays, including fear conditioning, decision-making in T-maze, open field, elevated plus maze, and novel object exploration. Calculates kinematic and postural statistics from keypoint tracking data from pose estimation software outputs.
Proper citation: BehaviorDEPOT (RRID:SCR_023602) Copy
https://github.com/DigitalHealthcareLab/22ActionRecognitionTool
Software tool for multi view child motor development dataset for AI-driven assessment of child development project.
Proper citation: 22ActionRecognitionTool (RRID:SCR_023552) Copy
https://github.com/fhcrc/seqmagick/
Software application to expose file format conversion in BioPython in convenient way. Imagemagick like frontend to Biopython SeqIO.
Proper citation: seqmagick (RRID:SCR_024331) Copy
https://github.com/WorkflowConversion/CTDopts
Software gives your command-line tools a CTD-compatible interface. Module for enabling tools with CTD reading/writing, argument parsing, validating and manipulating capabilities.
Proper citation: CTDopts (RRID:SCR_023997) Copy
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