๐ Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification
๐Journal: Clinical Epigenetics (I.F.=7.259)
๐Publish year: 2020
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #epigenetics
๐Journal: Clinical Epigenetics (I.F.=7.259)
๐Publish year: 2020
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #epigenetics
BioMed Central
Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification - Clinical Epigenetics
Background Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big dataโฆ
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๐จโ๐ซ Registration is open to One month International Bioinformatics Workshop by DE<code>LIFE
๐ฅ Epigenomics & Immunoinformatics - 4th Ed, 2023๐ฅ
๐ Duration: 14 March - 8 April, 2023
โ๏ธ Registration Link
https://decodelife.co.in
๐ฒ Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
๐ฅKey Features :
โซ๏ธ 23 sessions with approximately 35 hrs of learning.
โซ๏ธE- Certificate of Participation.
โน๏ธ video recording will be shared with participants immediately after each session along with relevant material.
โFrequently asked questions
https://decodelife.co.in/faq/
๐ฒChannel: @Bioinformatics
๐ฅ Epigenomics & Immunoinformatics - 4th Ed, 2023๐ฅ
๐ Duration: 14 March - 8 April, 2023
โ๏ธ Registration Link
https://decodelife.co.in
๐ฒ Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
๐ฅKey Features :
โซ๏ธ 23 sessions with approximately 35 hrs of learning.
โซ๏ธE- Certificate of Participation.
โน๏ธ video recording will be shared with participants immediately after each session along with relevant material.
โFrequently asked questions
https://decodelife.co.in/faq/
๐ฒChannel: @Bioinformatics
๐6
๐Interpretable machine learning for geneticists: opening the black box
๐Journal: Trends in Genetics (I.F.=11.821)
๐Publish year: 2020
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #machine_learning #genetics
๐Journal: Trends in Genetics (I.F.=11.821)
๐Publish year: 2020
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #machine_learning #genetics
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๐ Computational drug discovery and repurposing for the treatment of COVID-19: A systematic review
๐Journal: Bioorganic Chemistry (I.F.=5.307)
๐Publish year: 2021
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #drug_discovery #repurposing #covid19
๐Journal: Bioorganic Chemistry (I.F.=5.307)
๐Publish year: 2021
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #drug_discovery #repurposing #covid19
๐4
๐ Mapping miRNA Research in Schizophrenia: A Scientometric Review
๐Journal: International Journal of Molecular Sciences (I.F.=6.208)
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #miran #Schizophrenia
๐Journal: International Journal of Molecular Sciences (I.F.=6.208)
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #miran #Schizophrenia
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๐Ten simple rules for defining a computational biology project
๐ฅIf you are working in the field of computational biology, then hopefully you are familiar with the excitement associated with coming up with a new idea and thinking about how to follow up on it. Maybe the idea came from a talk you heard at a conference, a paper you read, or a conversation with a colleague. Regardless, your brain is now abuzz with how this idea will be implemented and what data youโll need to validate it. Ultimately, if your idea pans out, perhaps it will lead to profound scientific insights, a high-impact paper, and a widely used software tool. But for now, itโs just an idea in your head. How do you begin to bring your new idea to fruition? This is, of course, the core of the scientific methodโtransforming an idea (or hypothesis) into discoveries. Hence, your success as a scientist depends strongly on your ability to efficiently and effectively carry out such transformations.
Here, I focus on the very first few steps of that transformation, providing some general rules that can help start your new project in the right direction. Some of these rules may be considered variations on the questions asked in the Heilmeier catechism (https://www.darpa.mil/work-with-us/heilmeier-catechism), which is a set of questions that the US Defense Advanced Projects Agency uses to evaluate potential research projects.
๐Journal: PLOS Computational Biology (I.F.=4.779)
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
๐ฅIf you are working in the field of computational biology, then hopefully you are familiar with the excitement associated with coming up with a new idea and thinking about how to follow up on it. Maybe the idea came from a talk you heard at a conference, a paper you read, or a conversation with a colleague. Regardless, your brain is now abuzz with how this idea will be implemented and what data youโll need to validate it. Ultimately, if your idea pans out, perhaps it will lead to profound scientific insights, a high-impact paper, and a widely used software tool. But for now, itโs just an idea in your head. How do you begin to bring your new idea to fruition? This is, of course, the core of the scientific methodโtransforming an idea (or hypothesis) into discoveries. Hence, your success as a scientist depends strongly on your ability to efficiently and effectively carry out such transformations.
Here, I focus on the very first few steps of that transformation, providing some general rules that can help start your new project in the right direction. Some of these rules may be considered variations on the questions asked in the Heilmeier catechism (https://www.darpa.mil/work-with-us/heilmeier-catechism), which is a set of questions that the US Defense Advanced Projects Agency uses to evaluate potential research projects.
๐Journal: PLOS Computational Biology (I.F.=4.779)
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
๐5
๐ A review of data mining in bioinformatics
๐BSc Thesis from Centria University of Applied Sciences, Finland
๐Publish year: 2019
๐ Study thesis
๐ฒChannel: @Bioinformatics
#thesis #data_mining #review
๐BSc Thesis from Centria University of Applied Sciences, Finland
๐Publish year: 2019
๐ Study thesis
๐ฒChannel: @Bioinformatics
#thesis #data_mining #review
๐9
๐ Machine-Learning-Based Disease Diagnosis: A Comprehensive Review
๐Journal: Healthcare (I.F.=3.160)
๐Publish year: 2022
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #machine_learning #disease
๐Journal: Healthcare (I.F.=3.160)
๐Publish year: 2022
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #machine_learning #disease
๐7
๐ฅIntroduction to NCBI Pathogen Detection and antimicrobial resistance data in Google BigQuery๐ฅ
๐งโ๐ปFree webinar from NCBI
๐ Date: Mar 29, 2023
๐ Time: 12:00 PM in Eastern Time (US and Canada)
๐ Location: Online, Zoom
โ๐ป Details and Registration
๐ฒChannel: @Bioinformatics
#webinar #pathogen #google
๐งโ๐ปFree webinar from NCBI
๐ Date: Mar 29, 2023
๐ Time: 12:00 PM in Eastern Time (US and Canada)
๐ Location: Online, Zoom
โ๐ป Details and Registration
๐ฒChannel: @Bioinformatics
#webinar #pathogen #google
๐7๐ฅ5
๐Precision Medicine Informatics: Principles, Prospects, and Challenges
๐Journal: IEEE Access (I.F.=3.367)
๐Publish year: 2019
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #precision_medicine
๐Journal: IEEE Access (I.F.=3.367)
๐Publish year: 2019
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #precision_medicine
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๐A survey of the most recent Python packages for use in biology
๐Journal: NeuroQuantology
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #python
๐Journal: NeuroQuantology
๐Publish year: 2023
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #python
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๐Bioinformatics for RNAseq
๐ฅFree recorded workshop
๐ฝ Watch
๐ฒChannel: @Bioinformatics
#video #rnaseq
๐ฅFree recorded workshop
๐ฝ Watch
๐ฒChannel: @Bioinformatics
#video #rnaseq
YouTube
Bioinformatics for RNAseq
A recording of a live Zoom training for Bioinformatics for RNA Sequencing Analysis from the Tufts Data Lab, with Wenwen Hou, Rebecca Batorsky, and Albert Tai.
Recorded in May 2020.
Recorded in May 2020.
โค15๐6
๐Artificial intelligence in medical diagnostics: A review from a South African context
๐Journal: Scientific African
๐Publish year: 2022
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #ai #medical #african
๐Journal: Scientific African
๐Publish year: 2022
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #ai #medical #african
๐5
๐จโ๐ซA machine learning workshop with R
๐ฅTCGA Biomarkers Identification using Machine Learning๐ฅ
๐ Watch
โ๏ธ Slides
๐จโ๐ปCode
๐ฒChannel: @Bioinformatics
#video #machine_learning #biomarker #r
๐ฅTCGA Biomarkers Identification using Machine Learning๐ฅ
๐ Watch
โ๏ธ Slides
๐จโ๐ปCode
๐ฒChannel: @Bioinformatics
#video #machine_learning #biomarker #r
YouTube
TCGA Biomarkers Identification using Machine Learning | Complete Walkthrough
Well, mostly doing this since people have been asking to connect the database with some basic machine learning script , so I might as well capitalized on this. Anyhow, I mostly wrote this with the mindset on education and not really on research so the codeโฆ
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๐Deep learning: new computational modelling techniques for genomics
๐Journal: Nature Reviews Genetics (I.F.=59.94)
๐Publish year: 2019
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #deep_learning #genomics
๐Journal: Nature Reviews Genetics (I.F.=59.94)
๐Publish year: 2019
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #deep_learning #genomics
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๐ฅ Network Biology: Introduction to STRING and Cytoscape
๐จโ๐ซ Part of the "Statistical Methods in Bioinformatics" Ph.D. course offered by University of Copenhagen
๐ Watch
๐จโ๐ปAssociated hands-on exercises
๐ฒChannel: @Bioinformatics
#video #network_biology #STRING #Cytoscape
๐จโ๐ซ Part of the "Statistical Methods in Bioinformatics" Ph.D. course offered by University of Copenhagen
๐ Watch
๐จโ๐ปAssociated hands-on exercises
๐ฒChannel: @Bioinformatics
#video #network_biology #STRING #Cytoscape
YouTube
Network Biology: Introduction to STRING and Cytoscape
This lecture and software demo will cover the STRING database of protein interactions, related online database resources, the Cytoscape network analysis framework, and how the Cytoscape stringApp allows these to all be used together for omics data visualization.โฆ
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Forwarded from Network Analysis Resources & Updates
๐ Protein interaction networks: centrality, modularity, dynamics, and applications
๐Journal: Frontiers of Computer Science (I.F.=2.669)
๐Publish year: 2021
๐ Study the paper
๐ฒChannel: @ComplexNetworkAnalysis
#review #ppi
๐Journal: Frontiers of Computer Science (I.F.=2.669)
๐Publish year: 2021
๐ Study the paper
๐ฒChannel: @ComplexNetworkAnalysis
#review #ppi
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๐ฌ Using Python for cancer prediction by machine learning
๐ Watch
๐ฒChannel: @Bioinformatics
#video #cancer #python #machine_learning
๐ Watch
๐ฒChannel: @Bioinformatics
#video #cancer #python #machine_learning
YouTube
Machine learning for Cancer Prediction with Gene Expression Data | Random Forests | Python Tutorial
Cancer Prediction with Machine Learning
Consultation(Video Conferencing): https://calendly.com/bioinformaticscoach
Teaching(Video Conferencing): https://calendly.com/bioinformaticscoach
Consultation(Audio Call): https://clarity.fm/vincentappiah
Supportโฆ
Consultation(Video Conferencing): https://calendly.com/bioinformaticscoach
Teaching(Video Conferencing): https://calendly.com/bioinformaticscoach
Consultation(Audio Call): https://clarity.fm/vincentappiah
Supportโฆ
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๐ Machine learning for epigenetics and future medical applications
๐Journal: Epigenetics (I.F.=4.861)
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #epigenetics
๐Journal: Epigenetics (I.F.=4.861)
๐ Study the paper
๐ฒChannel: @Bioinformatics
#review #epigenetics
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