GitHub topics: target-prediction
AstraZeneca/biomedical-kg-topological-imbalance
Code to accompany the "Implications of Topological Imbalance for Representation Learning on Biomedical Knowledge Graphs" (Briefings in Bioinformatics, 2022)
Language: Jupyter Notebook - Size: 48.1 MB - Last synced at: about 14 hours ago - Pushed at: about 16 hours ago - Stars: 17 - Forks: 0
AstraZeneca/kgem-in-drug-discovery
Code to accompany the "Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery" manuscript (Artificial Intelligence in the Life Sciences, 2022)
Language: Python - Size: 268 KB - Last synced at: about 14 hours ago - Pushed at: about 16 hours ago - Stars: 33 - Forks: 6
ai4ce/EgoPAT3D
[CVPR 2022] Egocentric Action Target Prediction in 3D
Language: Jupyter Notebook - Size: 93.3 MB - Last synced at: 25 days ago - Pushed at: over 1 year ago - Stars: 32 - Forks: 3
lhm30/PIDGINv3
Protein target prediction using random forests and reliability-density neighbourhood analysis
Language: Python - Size: 5.27 MB - Last synced at: about 1 month ago - Pushed at: about 5 years ago - Stars: 40 - Forks: 14
metamaden/PrImiR 📦
Database of pairwise consensuses for miR-mRNA target interactions
Language: R - Size: 6.76 MB - Last synced at: 12 months ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 0
cvigilv/simspread
De novo target prediction by chemical similarity-guided network-based inference
Language: Julia - Size: 263 MB - Last synced at: about 2 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0
lhm30/PIDGINv2
PIDGIN Version 2: Prediction IncluDinG INactivity: Version 2 (LEGACY VERSION)
Language: Python - Size: 35.9 MB - Last synced at: about 1 month ago - Pushed at: almost 6 years ago - Stars: 30 - Forks: 8
ShirleyWISiu/LigTMap
LigTMap currently supports prediction for 17 protein target classes that include 6000+ protein targets.
Language: Python - Size: 703 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 13 - Forks: 8
Heidelberg-NLP/CO-NNECT Fork of maria-becker/CO-NNECT
This repository contains our path generation framework Co-NNECT, in which we combine two models for establishing knowledge relations and paths between concepts from sentences, as a form of explicitation of implicit knowledge: COREC-LM (COmmonsense knowledge RElation Classification using Language Models), a relation classification system that we developed for classifying commonsense knowledge relations; and COMET, a target prediction system developed by Bosselut et al., 2019.
Language: Python - Size: 2.32 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 9 - Forks: 1
BenderGroup/PIDGINv4
PIDGINv4
Language: Python - Size: 15.4 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 7 - Forks: 4
maria-becker/CO-NNECT
This repository contains our path generation framework Co-NNECT, in which we combine two models for establishing knowledge relations and paths between concepts from sentences, as a form of explicitation of implicit knowledge: COREC-LM (COmmonsense knowledge RElation Classification using Language Models), a relation classification system that we developed for classifying commonsense knowledge relations; and COMET, a target prediction system developed by Bosselut et al., 2019.
Language: Python - Size: 2.31 MB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 1 - Forks: 3
