π A Review of Approaches for Predicting DrugβDrug Interactions Based on Machine Learning
π Journal: Frontiers in Pharmacology (I.F.=5.6)
πPublish year: 2022
π Study
π²Channel: @Bioinformatics
#review #drug #machine_learning
π Journal: Frontiers in Pharmacology (I.F.=5.6)
πPublish year: 2022
π Study
π²Channel: @Bioinformatics
#review #drug #machine_learning
β€3π2
π A review and comparative study of cancer detection using machine learning
πJournal: BMC Bioinformatics (I.F.=3)
π Publish year: 2023
π§βπ»Authors: Mpho Mokoatle, Vukosi Marivate, Darlington Mapiye, Riana Bornman & Vanessa. M. Hayes
π’Universities: University of Pretoria, South Africa - CapeBio TM Technologies, Centurion, South Africa
π Study the paper
π²Channel: @Bioinformatics
#review #machine_learning #cancer
πJournal: BMC Bioinformatics (I.F.=3)
π Publish year: 2023
π§βπ»Authors: Mpho Mokoatle, Vukosi Marivate, Darlington Mapiye, Riana Bornman & Vanessa. M. Hayes
π’Universities: University of Pretoria, South Africa - CapeBio TM Technologies, Centurion, South Africa
π Study the paper
π²Channel: @Bioinformatics
#review #machine_learning #cancer
π1
Forwarded from Network Analysis Resources & Updates
π Machine Learning with Graphs: Graph Neural Networks in Computational Biology
π₯Free recorded course by Prof. Marinka Zitnik
π₯In this lecture, Prof. Marinka gives an overview of why graph learning techniques can greatly help with computational biology research. Concretely, this talk covers 3 exemplar use cases: (1) Discovering safe drug-drug combinations via multi-relational link prediction on heterogenous knowledge graphs; (2) Classify patient outcomes and diseases via learning subgraph embeddings; and (3) Learning effective disease treatments through few-shot learning for graphs.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #computational_biology
π₯Free recorded course by Prof. Marinka Zitnik
π₯In this lecture, Prof. Marinka gives an overview of why graph learning techniques can greatly help with computational biology research. Concretely, this talk covers 3 exemplar use cases: (1) Discovering safe drug-drug combinations via multi-relational link prediction on heterogenous knowledge graphs; (2) Classify patient outcomes and diseases via learning subgraph embeddings; and (3) Learning effective disease treatments through few-shot learning for graphs.
π½ Watch
π²Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #computational_biology
YouTube
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 18 - GNNs in Computational Biology
For more information about Stanfordβs Artificial Intelligence professional and graduate programs, visit: https://stanford.io/2XVImFC
Lecture 18 - Graph Neural Networks in Computational Biology
Jure Leskovec
Computer Science, PhD
We are glad to invite Prof.β¦
Lecture 18 - Graph Neural Networks in Computational Biology
Jure Leskovec
Computer Science, PhD
We are glad to invite Prof.β¦
π5β€1π1
π From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies
πJournal: Molecular Biotechnology (I.F.=2.6)
πPublish year: 2024
π§βπ»Authors: Arnab Mukherjee, Suzanna Abraham, Akshita Singh, ...
π’University: Manipal Institute of Technology, India
π Study the paper
π²Channel: @Bioinformatics
#review #omics #machine_learning
πJournal: Molecular Biotechnology (I.F.=2.6)
πPublish year: 2024
π§βπ»Authors: Arnab Mukherjee, Suzanna Abraham, Akshita Singh, ...
π’University: Manipal Institute of Technology, India
π Study the paper
π²Channel: @Bioinformatics
#review #omics #machine_learning
π8
πEmploying Machine Learning Techniques to Detect Protein Function: A Survey, Experimental, and Empirical Evaluations
π Publish year: 2024
π§βπ»Authors: Kamal Taha
π’University: Khalifa University, UAE
π Study the paper
π²Channel: @Bioinformatics
#review #protein #machine_learning
π Publish year: 2024
π§βπ»Authors: Kamal Taha
π’University: Khalifa University, UAE
π Study the paper
π²Channel: @Bioinformatics
#review #protein #machine_learning
π6
π Statistical and machine learning methods for cancer research and clinical practice: A systematic review
π Journal: Biomedical Signal Processing and Control (I.F.=4.9)
π Publish year: 2024
π§βπ»Authors: Laura Lopez-Perez, Eleni Georga, Carlo Conti, ...
π’Universities:
Universidad PolitΓ©cnica de Madrid, Spain
University of Ioannina, Greece
University of Milan, Italy
UniversitΓ‘ Campus Biomedico di Roma, Italy
π Study the paper
π²Channel: @Bioinformatics
#review #cancer #machine_learning
π Journal: Biomedical Signal Processing and Control (I.F.=4.9)
π Publish year: 2024
π§βπ»Authors: Laura Lopez-Perez, Eleni Georga, Carlo Conti, ...
π’Universities:
Universidad PolitΓ©cnica de Madrid, Spain
University of Ioannina, Greece
University of Milan, Italy
UniversitΓ‘ Campus Biomedico di Roma, Italy
π Study the paper
π²Channel: @Bioinformatics
#review #cancer #machine_learning
π4β€2π1
πApplication of Machine Learning in Systems Biology
πPhD Thesis form Chalmers University of Technology, Sweden
πPublish year: 2020
π Study thesis
π²Channel: @Bioinformatics
#thesis #machine_learning #systems_biology
πPhD Thesis form Chalmers University of Technology, Sweden
πPublish year: 2020
π Study thesis
π²Channel: @Bioinformatics
#thesis #machine_learning #systems_biology
β€8π2π1
πMachine Learning Models for the Identification of Prognostic and Predictive Cancer Biomarkers: A Systematic Review
πJournal: International Journal of Molecular Sciences (I.F.=4.9)
πPublish year: 2023
π§βπ»Authors: y Qasem Al-Tashi,Maliazurina B. Saad,Amgad Muneer, ...
π’University:
The University of Texas, USA
Torrens University Australia, Australia
Yonsei University, Republic of Korea
Obuda University, Hungary
π Study the paper
π²Channel: @Bioinformatics
#review #cancer #machine_learning #biomarker
πJournal: International Journal of Molecular Sciences (I.F.=4.9)
πPublish year: 2023
π§βπ»Authors: y Qasem Al-Tashi,Maliazurina B. Saad,Amgad Muneer, ...
π’University:
The University of Texas, USA
Torrens University Australia, Australia
Yonsei University, Republic of Korea
Obuda University, Hungary
π Study the paper
π²Channel: @Bioinformatics
#review #cancer #machine_learning #biomarker
β€4π1
π©βπ« Machine Learning and AI in Bioinformatics
π₯Texas A&M University
π©βπ» Course link
π²Channel: @Bioinformatics
#course #machine_learning #ai
π₯Texas A&M University
π©βπ» Course link
π²Channel: @Bioinformatics
#course #machine_learning #ai
π6π2
πA scoping review and bibliometric analysis (ScoRBA) of machine learning in genetic data analysis: unveiling the transformative potential
π Journal: Rwanda Medical Journal
πPublish year: 2024
π§βπ»Authors: Wan Nur Amalina Zakaria, Haikal Zahiruddin, ...
π’Universities: Universiti Teknologi MARA Kelantan, Malaysia - Universitas Indonesia Maju, Indonesia
π Study the paper
π²Channel: @Bioinformatics
#review #machine_learning #genetic
π Journal: Rwanda Medical Journal
πPublish year: 2024
π§βπ»Authors: Wan Nur Amalina Zakaria, Haikal Zahiruddin, ...
π’Universities: Universiti Teknologi MARA Kelantan, Malaysia - Universitas Indonesia Maju, Indonesia
π Study the paper
π²Channel: @Bioinformatics
#review #machine_learning #genetic
β€5π1