Fraunhofer SCAI Bioinformatics Department
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- SEEDS Public
SEEDS (Similarity based Expert Embedding Decision System) is a Retrieval-Augmented Generation (RAG) based agricultural question-answering (QA) system. It is built upon a domain-specific knowledge graph (KG), representing Cedar Apple Rust disease.
SCAI-BIO/SEEDS’s past year of commit activity - covid-NDD-comorbidity-NLP Public
This work aims to integrate diverse, curated biological databases with a comprehensive analysis of the growing body of literature on the potential long-term neurological consequences of COVID-19 infections, employing advanced natural language processing and text mining techniques.
SCAI-BIO/covid-NDD-comorbidity-NLP’s past year of commit activity - causal-npi-effects Public
A causal machine learning framework to assess effects of non-pharmaceutical interventions on pandemic disease spread.
SCAI-BIO/causal-npi-effects’s past year of commit activity - MMPK-SciML Public
Official implementation of the paper Scientific Machine learning for predicting plasma concentrations in anti-cancer therapy
SCAI-BIO/MMPK-SciML’s past year of commit activity