📃Temporal progress of gene expression analysis with RNA-Seq data: A review on the relationship between computational methods
📔Journal: Computational and Structural Biotechnology Journal (I.F.= 6)
🗓 Publish year: 2023
🧑💻Authors: Juliana Costa-Silva, Douglas S. Domingues, David Menotti, ...
🏢University: Federal University of Paraná, University of São Paulo, Universidade Tecnológica Federal do Paraná – UTFPR, Brzil
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📲Channel: @Bioinformatics
#review #rna_seq #gene_expression
📔Journal: Computational and Structural Biotechnology Journal (I.F.= 6)
🗓 Publish year: 2023
🧑💻Authors: Juliana Costa-Silva, Douglas S. Domingues, David Menotti, ...
🏢University: Federal University of Paraná, University of São Paulo, Universidade Tecnológica Federal do Paraná – UTFPR, Brzil
📎 Study the paper
📲Channel: @Bioinformatics
#review #rna_seq #gene_expression
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🎥 Analysis and Visualization of Protein-Ligand Interactions
🎞 Watch
📲Channel: @Bioinformatics
#video #protein #ligand
🎞 Watch
📲Channel: @Bioinformatics
#video #protein #ligand
YouTube
Analysis and Visualization of Protein-Ligand Interactions with PYMOL and PLIP
Welcome to Bioinformatics Insights. In this video, we will learn, How to analyze all types of protein-ligand interactions. I will also train you, How to visualize protein-ligand interactions using PYMOL. After watching this video, you will be able to analyze…
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📄 Application of Deep Learning on Single-Cell RNA Sequencing Data Analysis: A Review
📘Journal: Genomics, Proteomics and Bioinformatics (I.F.= 9.5)
🗓 Publish year: 2022
🧑💻Authors: Matthew Brendel, Chang Su, Zilong Bai, ...
🏢University: Cornell University - Temple University, USA
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📲Channel: @Bioinformatics
#review #deep_learning #single_cell #rna
📘Journal: Genomics, Proteomics and Bioinformatics (I.F.= 9.5)
🗓 Publish year: 2022
🧑💻Authors: Matthew Brendel, Chang Su, Zilong Bai, ...
🏢University: Cornell University - Temple University, USA
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📲Channel: @Bioinformatics
#review #deep_learning #single_cell #rna
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📃 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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📦 Related sources and contents
📲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.
📽 Watch
📲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.
📽 Watch
📲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
🎞 Watch
📲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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