📃Fifteen Years of Gene Set Analysis for High-Throughput Genomic Data: A Review of Statistical Approaches and Future Challenges
📘Journal: Entropy (I.F.=2.738)
🗓Publish year: 2020
📎 Study the paper
📲Channel: @Bioinformatics
#review #gene_set #genomic
📘Journal: Entropy (I.F.=2.738)
🗓Publish year: 2020
📎 Study the paper
📲Channel: @Bioinformatics
#review #gene_set #genomic
👍4❤1
📄A Survey of Machine Learning Approaches Applied to Gene Expression Analysis for Cancer Prediction
📘Journal: IEEE Access (I.F.=3.476)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #ml #gene_expression #cancer
📘Journal: IEEE Access (I.F.=3.476)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #ml #gene_expression #cancer
👍6
📑 A Survey of Biological Data in a Big Data Perspective
📘Journal: Big Data (I.F.=4.426)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #data #big_data
📘Journal: Big Data (I.F.=4.426)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #data #big_data
👍3
📃Genomics enters the deep learning era
📘Journal: PeerJ (I.F.=3.061)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #deep_learning #genomics
📘Journal: PeerJ (I.F.=3.061)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #deep_learning #genomics
👍4❤1
📄 Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review
📘Journal: Bioengineering (I.F.=5.046)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @Bioinformatics
#review #machine_learning #cancer #gene_expression
📘Journal: Bioengineering (I.F.=5.046)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @Bioinformatics
#review #machine_learning #cancer #gene_expression
👍7
📃The application of machine learning to multi-omics data: dealing with dimensionality
📘Journal: Briefing in Bioinformatics (I.F.=13.994)
🗓Publish year: 2023
📎 Study the paper
💾 Data and processing scripts
📲Channel: @Bioinformatics
#review #machine_learning #multi_omics
📘Journal: Briefing in Bioinformatics (I.F.=13.994)
🗓Publish year: 2023
📎 Study the paper
💾 Data and processing scripts
📲Channel: @Bioinformatics
#review #machine_learning #multi_omics
👍8
📑Ten simple rules for teaching yourself R
💥Teaching yourself new skills can be hard. It can be a process rife with frustration, self-doubt, and low motivation to continue. The 10 rules we list here are our best strategies to overcome these challenges, master new techniques, and maybe even have some fun along the way! We hope that these rules will help new R users, be they graduate students, hobbyists, or established researchers eager to learn a new tool.
📘Journal: PLOS Computational Biology (I.F.=4.779)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#r
💥Teaching yourself new skills can be hard. It can be a process rife with frustration, self-doubt, and low motivation to continue. The 10 rules we list here are our best strategies to overcome these challenges, master new techniques, and maybe even have some fun along the way! We hope that these rules will help new R users, be they graduate students, hobbyists, or established researchers eager to learn a new tool.
📘Journal: PLOS Computational Biology (I.F.=4.779)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#r
👍7❤3
📄Comprehensive Review of Web Servers and Bioinformatics Tools for Cancer Prognosis Analysis
📘Journal: Frontiers in Oncology (I.F.=5.738)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #cancer #tool #web
📘Journal: Frontiers in Oncology (I.F.=5.738)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #cancer #tool #web
👍7👌1
📃Towards reproducible computational drug discovery
📘Journal: Journal of Cheminformatics (I.F.=8.469)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
#review #drug_discovery
📘Journal: Journal of Cheminformatics (I.F.=8.469)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
#review #drug_discovery
👍6👌3❤2
📑 Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification
📘Journal: Clinical Epigenetics (I.F.=7.259)
🗓Publish year: 2020
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📲Channel: @Bioinformatics
#review #epigenetics
📘Journal: Clinical Epigenetics (I.F.=7.259)
🗓Publish year: 2020
📎 Study the paper
📲Channel: @Bioinformatics
#review #epigenetics
SpringerLink
Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification
Clinical Epigenetics - 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...
👍12❤3
👨🏫 Registration is open to One month International Bioinformatics Workshop by DE<code>LIFE
💥 Epigenomics & Immunoinformatics - 4th Ed, 2023💥
🗓 Duration: 14 March - 8 April, 2023
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features :
▫️ 23 sessions with approximately 35 hrs of learning.
▫️E- Certificate of Participation.
ℹ️ video recording will be shared with participants immediately after each session along with relevant material.
❔Frequently asked questions
https://decodelife.co.in/faq/
📲Channel: @Bioinformatics
💥 Epigenomics & Immunoinformatics - 4th Ed, 2023💥
🗓 Duration: 14 March - 8 April, 2023
✍️ Registration Link
https://decodelife.co.in
💲 Fees: Rupees 1200 for Indian Participants /USD 25 for international Participants
💥Key Features :
▫️ 23 sessions with approximately 35 hrs of learning.
▫️E- Certificate of Participation.
ℹ️ video recording will be shared with participants immediately after each session along with relevant material.
❔Frequently asked questions
https://decodelife.co.in/faq/
📲Channel: @Bioinformatics
👍6
📃Interpretable machine learning for geneticists: opening the black box
📘Journal: Trends in Genetics (I.F.=11.821)
🗓Publish year: 2020
📎 Study the paper
📲Channel: @Bioinformatics
#review #machine_learning #genetics
📘Journal: Trends in Genetics (I.F.=11.821)
🗓Publish year: 2020
📎 Study the paper
📲Channel: @Bioinformatics
#review #machine_learning #genetics
👍3❤2👌2
📄 Computational drug discovery and repurposing for the treatment of COVID-19: A systematic review
📘Journal: Bioorganic Chemistry (I.F.=5.307)
🗓Publish year: 2021
📎 Study the paper
📲Channel: @Bioinformatics
#review #drug_discovery #repurposing #covid19
📘Journal: Bioorganic Chemistry (I.F.=5.307)
🗓Publish year: 2021
📎 Study the paper
📲Channel: @Bioinformatics
#review #drug_discovery #repurposing #covid19
👍4
📃 Mapping miRNA Research in Schizophrenia: A Scientometric Review
📘Journal: International Journal of Molecular Sciences (I.F.=6.208)
🗓Publish year: 2023
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📲Channel: @Bioinformatics
#review #miran #Schizophrenia
📘Journal: International Journal of Molecular Sciences (I.F.=6.208)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @Bioinformatics
#review #miran #Schizophrenia
👍4💯1
📄Ten simple rules for defining a computational biology project
💥If 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 you’ll 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, it’s 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 method–transforming 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.
📘Journal: PLOS Computational Biology (I.F.=4.779)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @Bioinformatics
💥If 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 you’ll 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, it’s 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 method–transforming 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.
📘Journal: PLOS Computational Biology (I.F.=4.779)
🗓Publish year: 2023
📎 Study the paper
📲Channel: @Bioinformatics
👍5
🎓 A review of data mining in bioinformatics
📘BSc Thesis from Centria University of Applied Sciences, Finland
🗓Publish year: 2019
📎 Study thesis
📲Channel: @Bioinformatics
#thesis #data_mining #review
📘BSc Thesis from Centria University of Applied Sciences, Finland
🗓Publish year: 2019
📎 Study thesis
📲Channel: @Bioinformatics
#thesis #data_mining #review
👍9
📃 Machine-Learning-Based Disease Diagnosis: A Comprehensive Review
📘Journal: Healthcare (I.F.=3.160)
🗓Publish year: 2022
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📲Channel: @Bioinformatics
#review #machine_learning #disease
📘Journal: Healthcare (I.F.=3.160)
🗓Publish year: 2022
📎 Study the paper
📲Channel: @Bioinformatics
#review #machine_learning #disease
👍7
💥Introduction to NCBI Pathogen Detection and antimicrobial resistance data in Google BigQuery💥
🧑💻Free webinar from NCBI
🗓 Date: Mar 29, 2023
🕖 Time: 12:00 PM in Eastern Time (US and Canada)
📍 Location: Online, Zoom
✍🏻 Details and Registration
📲Channel: @Bioinformatics
#webinar #pathogen #google
🧑💻Free webinar from NCBI
🗓 Date: Mar 29, 2023
🕖 Time: 12:00 PM in Eastern Time (US and Canada)
📍 Location: Online, Zoom
✍🏻 Details and Registration
📲Channel: @Bioinformatics
#webinar #pathogen #google
👍7🔥5
📑Precision Medicine Informatics: Principles, Prospects, and Challenges
📘Journal: IEEE Access (I.F.=3.367)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #precision_medicine
📘Journal: IEEE Access (I.F.=3.367)
🗓Publish year: 2019
📎 Study the paper
📲Channel: @Bioinformatics
#review #precision_medicine
👍7🤔2