Forwarded from Network Analysis Resources & Updates
🎞 Introduction to Brain Network Analysis
💥Free recorded Lecture by Dr. Johann D. Kruschwitz.
💥Graph Theoretical Modelling of Brain Connectivity.
📽 Watch: part1 part2
📲Channel: @ComplexNetworkAnalysis
#video #Lecture #Brain
💥Free recorded Lecture by Dr. Johann D. Kruschwitz.
💥Graph Theoretical Modelling of Brain Connectivity.
📽 Watch: part1 part2
📲Channel: @ComplexNetworkAnalysis
#video #Lecture #Brain
YouTube
Introduction to Brain Network Analysis - Part 1/2.
Introduction to Brain Network Analysis - Part 1/2. Graph Theoretical Modelling of Brain Connectivity. Concepts and Workflow. GraphVar by Dr. Johann D. Kruschwitz.
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📄Graph Representation Learning in Biomedicine
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#graph #biomedicine
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#graph #biomedicine
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🎞Sequencing Data Analysis: Introduction to Key Concepts
💥Topics:
▫️Experimental design
▫️Key bioinformatics concepts such as alignment, variant calling, de novo assembly and RNA Seq analysis
▫️Highlight Illumina software tools used in these pipelines
📽 Watch
📲Channel: @Bioinformatics
#video
💥Topics:
▫️Experimental design
▫️Key bioinformatics concepts such as alignment, variant calling, de novo assembly and RNA Seq analysis
▫️Highlight Illumina software tools used in these pipelines
📽 Watch
📲Channel: @Bioinformatics
#video
YouTube
Sequencing Data Analysis: Introduction to Key Concepts
This webinar is intended to introduce key data analysis and bioinformatics concepts used in analysis of Illumina sequencing data. This webinar is targeted for those that are new or intermediate to Illumina Next Generation Sequencing analysis, specifically…
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition (2022)
🔗 Download Link:
https://filewebster.com/files/download/MTY1MzcyNzM1OF8yNTc5
✅ Our Channels 👇👇👇
1⃣ @DataScience_Books
2⃣ @CodeProgrammer
🔗 Download Link:
https://filewebster.com/files/download/MTY1MzcyNzM1OF8yNTc5
✅ Our Channels 👇👇👇
1⃣ @DataScience_Books
2⃣ @CodeProgrammer
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📑Computational medicine: quantitative modeling of complex diseases
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #medicine #diease
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #medicine #diease
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🎓Predicting potential drugs and drug-drug interactions for drug repositioning
📘PhD's thesis from University of Saskatchewan, Canada
🗓Publish year: 2022
📎Study thesis
📲Channel: @Bioinformatics
#thesis #drug
📘PhD's thesis from University of Saskatchewan, Canada
🗓Publish year: 2022
📎Study thesis
📲Channel: @Bioinformatics
#thesis #drug
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📃Challenges and Limitations of Biological Network Analysis
📘Journal: BioTech
🗓Publish year: 7 July 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #ppi #pathways
📘Journal: BioTech
🗓Publish year: 7 July 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #ppi #pathways
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📑 A guide to performing systematic literature reviews in bioinformatics
📘Publisher: Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Federal University of Minas Gerais, Brazil
📎 Study the paper
📲Channel: @Bioinformatics
#guide #review
📘Publisher: Laboratory of Bioinformatics and Systems (LBS), Department of Computer Science, Federal University of Minas Gerais, Brazil
📎 Study the paper
📲Channel: @Bioinformatics
#guide #review
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Forwarded from Network Analysis Resources & Updates
2020_A_paradigm_shift_in_medicine_A_comprehensive_review_of_network.pdf
1.3 MB
📄A paradigm shift in medicine: A comprehensive review of network-based approaches
📘Journal: Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms (I.F=6.304 )
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #medicine #review
📘Journal: Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms (I.F=6.304 )
🗓Publish year: 2020
📎 Study paper
📱Channel: @ComplexNetworkAnalysis
#paper #medicine #review
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👨🏫 Registration is open to Joint one month Bioinformatics Workshop by DE<code>LIFE 🧬 and Premas Life Sciences Private limited.
💥 Next Generation Sequencing Analysis 💥
🗓 Duration: 22 July- 18 August, 2022
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features:
▫️ 21 sessions with approximately 30 hrs of learning.
▫️E- Certificate of Participation.
❓ Frequently asked questions
https://decodelife.co.in/faq/
📲Channel: @Bioinformatics
💥 Next Generation Sequencing Analysis 💥
🗓 Duration: 22 July- 18 August, 2022
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features:
▫️ 21 sessions with approximately 30 hrs of learning.
▫️E- Certificate of Participation.
❓ Frequently asked questions
https://decodelife.co.in/faq/
📲Channel: @Bioinformatics
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📃Data mining in clinical big data: the frequently used databases, steps, and methodological models
📘Journal: Military Medical Research (I.F.=34.915)
🗓Publish year: 2021
📎 Study the paper
📲Channel: @Bioinformatics
#review #clinical #data_mining
📘Journal: Military Medical Research (I.F.=34.915)
🗓Publish year: 2021
📎 Study the paper
📲Channel: @Bioinformatics
#review #clinical #data_mining
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📃Personal Health Records: A Systematic Literature Review
📘Journal: Journal of Medical Internet Research (I.F.=7.076)
🗓Publish year: 2017
📎 Study the paper
📲Channel: @Bioinformatics
#review #phr
📘Journal: Journal of Medical Internet Research (I.F.=7.076)
🗓Publish year: 2017
📎 Study the paper
📲Channel: @Bioinformatics
#review #phr
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📕Tutorial series for visualizing and interpreting omic data
🌐 Go to website
📲Channel: @Bioinformatics
#visualization #omic
🌐 Go to website
📲Channel: @Bioinformatics
#visualization #omic
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📑Feature selection methods and genomic big data: a systematic review
📘Journal: Journal of Big Data (I.F.=10.835)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #genomic #feature_selection
📘Journal: Journal of Big Data (I.F.=10.835)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #genomic #feature_selection
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📓 An Introduction to Applied Bioinformatics
💥Free online book with python examples
🌐 Study the book
📲Channel: @Bioinformatics
#book #python
💥Free online book with python examples
🌐 Study the book
📲Channel: @Bioinformatics
#book #python
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📃Impact of computational approaches in the fight against COVID-19: an AI guided review of 17000 studies
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #covid-19
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #covid-19
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📃Interpretation of differential gene expression results of RNA-seq data: review and integration
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2019
💥Abstract:
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.
📎 Study the paper
📲Channel: @Bioinformatics
#review #DEG
📘Journal: Briefings in Bioinformatics (I.F.=13.994)
🗓Publish year: 2019
💥Abstract:
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.
📎 Study the paper
📲Channel: @Bioinformatics
#review #DEG
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🎞Accelerating Drug Discovery with Machine Learning and AI
💥Recorded Seminar
📽 Watch
📲Channel: @Bioinformatics
#video #drug #ai
💥Recorded Seminar
📽 Watch
📲Channel: @Bioinformatics
#video #drug #ai
YouTube
Olexandr Isayev - Accelerating Drug Discovery with Machine Learning and AI
Presented on 2/4/2021
Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition, and computer vision. In this talk, we will provide an overview of the latest developments of machine…
Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition, and computer vision. In this talk, we will provide an overview of the latest developments of machine…
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