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http://sourceforge.net/projects/bycom/

A software which can perform methylcytosine calling from BS-seq (WGBS and RRBS), and permits either unmapped reads (FASTQ) or mapped reads (SAM/BAM) to be used as the input data. Certain SNPs (C>A/G) can also be selected in the output.

Proper citation: Bycom (RRID:SCR_000659) Copy   

•   Source: SciCrunch Registry

https://stattech.ru

Web service for statistics with automated data analysis mode.

Proper citation: StatTech (RRID:SCR_023071) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FB-BT

A structured controlled vocabulary of the anatomy of Drosophila melanogaster.

Proper citation: Drosophila Gross Anatomy Ontology (RRID:SCR_010311) Copy   

•   Source: SciCrunch Registry

https://github.com/Lcornet/GENERA

Software toolbox to infer completely reproducible comparative genomic and metabolic analyses on prokaryotes and small eukaryotes.

Proper citation: GENERA (RRID:SCR_023113) Copy   

•   Source: SciCrunch Registry

https://github.com/plaisier-lab/OncoMerge

Software tool to integrate somatic mutation types into comprehensive integrated somatic mutation matrix for downstream analyses.Somatic mutation integration platform that tames allelic heterogeneity, discovers causal mutations, integrates binary PAM and fusion with quantitative CNA data types, and overcomes known obstacles in cancer genetics. Used for systematic integration of protein affecting mutations, gene fusions, and copy number alterations into comprehensive somatic mutational profile.

Proper citation: OncoMerge (RRID:SCR_023079) Copy   

•   Source: SciCrunch Registry

http://ohnlp.org/index.php/ICEPO

An ontology distributed in OWL format which contains comprehensive terms describing ion channel electrophysiology. Terms from related ontologies, such as Cell Physiology Ontology (CPO), Cardiac Electrophysiology Ontology (CEPO), and Unit Ontology, were integrated into ICEPO.

Proper citation: ICEPO (RRID:SCR_014359) Copy   

•   Source: SciCrunch Registry

https://www.distillersr.com/products/distillersr-systematic-review-software

Literature review software by DistillerSR Inc. Automates management of literature collection, screening, and assessment using AI and intelligent workflows. From systematic literature review to rapid review to living review, makes any project simpler to manage and configure to produce transparent, audit-ready, and compliant results.

Proper citation: DistillerSR (RRID:SCR_023078) Copy   

•   Source: SciCrunch Registry

http://prime.psc.riken.jp/compms/msdial/main.html

Software tool for data independent MS/MS deconvolution for comprehensive metabolome analysis. Universal program for untargeted metabolomics that supports multiple instruments (GC/MS, GC/MS/MS, LC/MS, and LC/MS/MS) and MS vendors (Agilent, Bruker, LECO, Sciex, Shimadzu, Thermo, and Waters). Used for untargeted metabolomics and lipidomics supporting any type of chromatography/mass spectrometry methods.

Proper citation: MS-DIAL (RRID:SCR_023076) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/FIX

Two ontologies: methods and properties (but not objects, which are subject of the chemical ontology). The methods are applied to study the properties.

Proper citation: Physico-Chemical Methods and Properties (RRID:SCR_010407) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/SSO

Ontology that encodes agreement among experts about how Emergency Department (ED) chief complaints are grouped into syndromes of public health importance (consensus definitions).

Proper citation: Syndromic Surveillance Ontology (RRID:SCR_010409) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ORDO

Ontology to provide a structured vocabulary for rare diseases capturing relationships between diseases, genes and other relevant features which will form a useful resource for the computational analysis of rare diseases. It derived from the Orphanet database (http://www.orpha.net) , a multilingual database dedicated to rare diseases populated from literature and validated by international experts. It integrates a nosology (classification of rare diseases), relationships (gene-disease relations, epiemological data) and connections with other terminologies (MeSH, SNOMED CT, UMLS, MedDRA), databases (OMIM, UniProtKB, HGNC, ensembl, Reactome, IUPHAR, Geantlas) or classifications (ICD10). The ontology will be maintained by Orphanet and further populated with new data. Orphanet classifications can be browsed in the OLS view. The Orphanet Rare Disease Ontology is updated monthly and follows the OBO guidelines on deprecation of terms. It constitutes the official ontology of rare diseases produced and maintained by Orphanet (INSERM, US14).

Proper citation: Orphanet Rare Disease Ontology (RRID:SCR_010402) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/PEO

Ontology that models provenance metadata associated with experiment protocols used in parasite research. The PEO extends the upper-level Provenir ontology (http://knoesis.wright.edu/provenir/provenir.owl) to represent parasite domain-specific provenance terms. The PEO (v 1.0) includes Proteome, Microarray, Gene Knockout, and Strain Creation experiment terms along with other terms that are used in pathway.

Proper citation: Parasite Experiment Ontology (RRID:SCR_010403) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/PHARE

Ontology that proposes concepts and roles to represent relationships of pharmacogenomics interest.

Proper citation: Pharmacogenomic Relationships Ontology (RRID:SCR_010406) Copy   

•   Source: SciCrunch Registry

http://sbi.postech.ac.kr/oasis/introduction/

A tool for various statistical tasks involved in analyzing survival data which provides a uniform platform to facilitate efficient statistical analyses of survival data in the aging field. The statistical features of OASIS include the calculation of Kaplan-Meier estimates, mean/median lifespan, mortality rate, Mantel-Cox Log-Rank test, Fishers exact test, weighted Log-Rank test, Kolmogorov-Smirnov test and Neymans smooth test. Moreover, OASIS generates survival and mortality curves that can be easily exported and modified by using common graphic softwares.

Proper citation: Online Application for Survival Analysis (OASIS) (RRID:SCR_014450) Copy   

•   Source: SciCrunch Registry

http://labs.europepmc.org/evf

A web application to assist in the identification of articles and research related to literature search terms. The search covers full text articles in the Europe PMC repository. Relevant papers are suggested to users based on the scientific term searched and the selection of questions, generated by the application, relevant to term searched.

Proper citation: EvidenceFinder (RRID:SCR_013764) Copy   

•   Source: SciCrunch Registry

http://neurolog.i3s.unice.fr/public_namespace/ontology

An ontology for neuroimaging or medical imaging studies based on DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. Detailed description from web: Our aim is the design of a common semantic model providing a unified view on all data and tools to be shared between NeuroLOG partners. For this purpose, we built a multi-layered and multi-components formal ontology. We chose a design framework that structures the ontology at different levels of abstraction while respecting common conceptualization choices. At the highest level is a top-level ontology that includes abstract concepts and relationships valid across domains. We adopted DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering), as the foundational ontology. We then added Core ontologies, which provide generic, basic and minimal concepts and relations in a specific domain. By minimal we mean that core ontologies should include only the most reusable and widely applicable categories. These kinds of ontologies are essential for sharing intended meaning between different domains. We adopted I& DA (Information and Discourse Acts), a core ontology initially built for classifying documents as a function of their content.We use it to model medical images, which we consider as types of documents. Participant Roles is the core ontology we use to describe the modes of image participation in data processing. I& DA and Participant Roles are built according to DOLCE ontological commitments. On the basis of these two layers, we constructed our Domain ontology dedicated to conceptualizing a specific domain, in this case neuroimaging. Obviously, large domains such as neuroimaging can be divided into sub-domains for the sake of modularization.

Proper citation: OntoNeuroLOG (RRID:SCR_008957) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/DDI

Ontology for the description of drug discovery investigations. DDI aims to follow to the OBO (Open Biomedical Ontologies) Foundry principles, uses relations laid down in the OBO Relation Ontology, and be compliant with Ontology for biomedical investigations (OBI).

Proper citation: Ontology for Drug Discovery Investigations (RRID:SCR_010383) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/OGSF

Application ontology to model / represent the notion of genetic susceptibility to a specific disease or an adverse event or a pathological biological process. It is developed using BFO2.0''s framwork. The ontology is under the domain of genetic epidemiology.

Proper citation: Ontology for Genetic Susceptibility Factor (RRID:SCR_010386) Copy   

•   Source: SciCrunch Registry

http://www.cbs.dtu.dk/services/SignalP/

Web application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.

Proper citation: SignalP (RRID:SCR_015644) Copy   

•   Source: SciCrunch Registry

http://purl.bioontology.org/ontology/ACGT-MO

Ontology to represent the domain of cancer research and management in a computationally tractable manner.

Proper citation: Cancer Research and Management ACGT Master Ontology (RRID:SCR_006953) Copy   

•   Source: SciCrunch Registry