📃 Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey
🗓 Publish year: 2024
🧑💻Authors: Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, ...
🏢University: Renmin University of China, University of Science and Technology of China, Microsoft Research
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📲Channel: @Bioinformatics
#review #nlp #biomolecule #protein
🗓 Publish year: 2024
🧑💻Authors: Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, ...
🏢University: Renmin University of China, University of Science and Technology of China, Microsoft Research
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📦 Related sources and contents
📲Channel: @Bioinformatics
#review #nlp #biomolecule #protein
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📑 Ten simple rules for designing graphical abstracts
📕Journal: Plos Computational Biology (I.F.=4.3)
🗓Publish year: 2024
🧑💻Authors: Helena Klara Jambor ,Martin Bornhäuser
🏢University: Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Germany
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📲Channel: @Bioinformatics
#graphical_abstract
📕Journal: Plos Computational Biology (I.F.=4.3)
🗓Publish year: 2024
🧑💻Authors: Helena Klara Jambor ,Martin Bornhäuser
🏢University: Universitätsklinikum Carl Gustav Carus an der Technischen Universität Dresden, Germany
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📲Channel: @Bioinformatics
#graphical_abstract
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📑 Explainable artificial intelligence for omics data: a systematic mapping study
📗Journal: Briefings in Bioinformatics (I.F.=9.5)
🗓Publish year: 2024
🧑💻Authors: Philipp A Toussaint, Florian Leiser, Scott Thiebes, ...
🏢University: Department of Economics and Management - University of Augsburg , Germany
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📲Channel: @Bioinformatics
#review #explainable #ai #omics
📗Journal: Briefings in Bioinformatics (I.F.=9.5)
🗓Publish year: 2024
🧑💻Authors: Philipp A Toussaint, Florian Leiser, Scott Thiebes, ...
🏢University: Department of Economics and Management - University of Augsburg , Germany
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📲Channel: @Bioinformatics
#review #explainable #ai #omics
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📃 Recent Advances in Generative Adversarial Networks for Gene Expression Data: A Comprehensive Review
📗Journal: Mathematics (I.F.=2.4)
🗓Publish year: 2023
🧑💻Authors: Minhyeok Lee
🏢University: Chung-Ang University, Republic of Korea
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📲Channel: @Bioinformatics
#review #GAN #gene_expression
📗Journal: Mathematics (I.F.=2.4)
🗓Publish year: 2023
🧑💻Authors: Minhyeok Lee
🏢University: Chung-Ang University, Republic of Korea
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📲Channel: @Bioinformatics
#review #GAN #gene_expression
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Forwarded from Network Analysis Resources & Updates
🎞 Machine Learning with Graphs: Graph Neural Networks in Computational Biology
💥Free recorded course by Prof. Marinka Zitnik
💥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.
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📲Channel: @ComplexNetworkAnalysis
#video #course #Graph #GNN #Machine_Learning #computational_biology
💥Free recorded course by Prof. Marinka Zitnik
💥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.
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📲Channel: @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 Stanford’s 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.…
Lecture 18 - Graph Neural Networks in Computational Biology
Jure Leskovec
Computer Science, PhD
We are glad to invite Prof.…
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📹 The intersection of Bioinformatics, Machine learning, and scientific experimentation
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📲Channel: @Bioinformatics
#video #pharmacology
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📲Channel: @Bioinformatics
#video #pharmacology
YouTube
The intersection of Bioinformatics, Machine learning, and scientific experimentation with Rahul Jose
In the 23rd episode of The AI Digest Podcast, we delve into the evolving field of pharmacology and gain valuable perspectives on pursuing impactful work in drug discovery and patient care through diverse pathways in the innovative biopharmaceutical domain.…
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📃 In silico protein function prediction: the rise of machine learning-based approaches
📙Journal: Medical Review (De Gruyter)
🗓Publish year: 2023
🧑💻Authors: Jiaxiao Chen , Zhonghui Gu , Luhua Lai, Jianfeng Pei
🏢University: Peking University, China
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📲Channel: @Bioinformatics
#review #protein_function #ml
📙Journal: Medical Review (De Gruyter)
🗓Publish year: 2023
🧑💻Authors: Jiaxiao Chen , Zhonghui Gu , Luhua Lai, Jianfeng Pei
🏢University: Peking University, China
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📲Channel: @Bioinformatics
#review #protein_function #ml
👍6❤1
📃 From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies
📘Journal: Molecular Biotechnology (I.F.=2.6)
🗓Publish year: 2024
🧑💻Authors: Arnab Mukherjee, Suzanna Abraham, Akshita Singh, ...
🏢University: Manipal Institute of Technology, India
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📲Channel: @Bioinformatics
#review #omics #machine_learning
📘Journal: Molecular Biotechnology (I.F.=2.6)
🗓Publish year: 2024
🧑💻Authors: Arnab Mukherjee, Suzanna Abraham, Akshita Singh, ...
🏢University: Manipal Institute of Technology, India
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📲Channel: @Bioinformatics
#review #omics #machine_learning
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