20 skills found
MannLabs / CKGClinical Knowledge Graph (CKG) is a platform with twofold objective: 1) build a graph database with experimental data and data imported from diverse biomedical databases 2) automate knowledge discovery making use of all the information contained in the graph
MedSegX / MedSegX Code[nature biomedical engineering 2025] Official code for paper: A generalist foundation model and database for open-world medical image segmentation (MedSegX)
YuxingLu613 / Awesome Biomedical Knowledge GraphsA curated list of Biomedical Knowledge Graph related learning materials, databases, tools and other resources
xMAnton / BioGraknA Knowledge Graph-based Semantic Database for Biomedical Sciences
JuliaHealth / BioMedQuery.jlJulia utilities for interacting with biomedical databases and biomedical application programming interfaces (APIs)
pascalwhoop / Medical McpsA collection of MCP tools for AI agents to interact with major biomedical databases
tamerh / BiobtreeBioBTree v2: An MCP-enabled biomedical graph database unifying 50+ datasets.
rubalsxngh / MedGraph Biomedical Knowledge Graph With Mondo OntologyMedGraph is a project focused to construct biomedical knowledge graph. It harnesses the power of pubMed for data retrieval, spaCy for NLP, Mondo Ontology for semantic enrichment, and pywikibot for integrating external knowledge. The final step involves deploying the graph onto the Neo4j database, creating a platform to explore medical information.
svcvit / Dify Plugin PubmedThis Dify plugin provides tools to interact with the National Library of Medicine's PubMed database, allowing users to search for biomedical literature and analyze the results directly within Dify workflows.
BrianPulfer / AuthorNameDisambiguationAn AND implementation for biomedical articles from PubMed database
RTXteam / PloverDBAn in-memory database service for hosting and serving biomedical knowledge graphs as TRAPI APIs
bhklab / PredictionetThis package contains a set of functions related to network inference combining genomic data and prior information extracted from biomedical literature and structured biological databases.The main function is able to generate networks using bayesian or regression-based inference methods; while the former is limited to < 100 of variables, the latter may infer network with hundreds of variables. Several statistics at the edge and node levels have been implemented (edge stability, predictive ability of each node, ...) in order to help the user to focus on high quality subnetworks. Ultimately, this package is used in the 'Predictive Networks' web application developed by the Dana-Farber Cancer Institute in collaboration with Entagen
NCIP / Nci Metathesaurus BrowserThe NCI Metathesaurus (NCIm) Browser is a web-based terminology browser that allows users to browse and search the NCI Metathesaurus, a biomedical terminology database that maps terms from more than 70 terminology sources into some 1.5 million biomedical concepts.
tasosnent / BiomedicalHarvestersHarvesting knowledge from different biomedical resources (PubMed, PMC, OBO ontologies, DrugBank) into colletions of a MongoDB database.
reyesaldasoro / PubMed Data Mining And VisualisationVisualisation and data mining of the public database of biomedical literature PubMed
Superraptor / GnomicsA comprehensive search for biomedical and biological databases.
Wang-Lin-boop / Biodb SearchA user-friendly biomedical database integration interface.
Jawad-Dar / Spectral Topographies And Optimal Hierarchical Attention Networks For Pulmonary Abnormality DetectioWCSO-HAN :Spectral topographies and optimal Hierarchical Attention Networks for Pulmonary abnormality detection from the Respiratory Sound signals. The experimentation of the developed technique is performed in PYTHON tool by International Conference in Biomedical and Health Informatics (ICBHI 2017) (dataset-1) and respiratory sound database (dataset-2) [and for the efficient pulmonary abnormality detection
AristeaKoutroumani / Covid 19 Knowledge GraphThe process that was developed provides a way to access a public repository of biomedical papers (PubMed) using its API for Python (PyMed) and extract information on a topic (Covid-19) that is processed using Natural Language Processing (NLP) techniques to extract semantic triplets in the format of “subject, predicate, object”. The software that is used for the semantic triplet extractions is SemRep, a UMLS-based program that extracts three-part propositions, called semantic predications from sentences in biomedical text. Additional processing is performed by implementing various techniques of data mining to generate and maintain additional information for the origin and the quality of those semantic triplets. This information is then stored in a graph database (Neo4J), which can be explored using a query language (Cypher) and presented in a way that is easy to understand and use for anyone. This process can be used to aid researchers in their expedition of research into Covid-19. The most important findings of the reasearch were the corellation among critical aspects of covid-19, along with its relevant/accurate source for further investigation. Considering that the study and analysis of how language is used figuratively and literally is proven to be a challenging task, the outcome of this project can serve clinicians needs and it can be easily adjusted to provide insightful data for any other medical topic. Keywords: covid-19, graph databases, data mining ,semantic predications, pubmed, semrep, neo4j,cypher
LLancelot / Pubmed Articles ChatbotA chatbot application for searching Pubmed articles (accessing primarily the MEDLINE database of references and abstracts on life sciences and biomedical topics).
