👨🏫 Biology and Data Science - Bioinformatics in action
Free webinar from Helsinki center for data science
🗓 Tuesday 30.3.2021, 9:00–11:00
✍️ Registration:
https://www.lyyti.in/hidata_bioinformatics
ℹ️Webinar program and more about the speakers:
https://www2.helsinki.fi/en/news/data-science-news/hidata-webinar-on-bioinformatics
📲Channel: @Bioinformatics
Free webinar from Helsinki center for data science
🗓 Tuesday 30.3.2021, 9:00–11:00
✍️ Registration:
https://www.lyyti.in/hidata_bioinformatics
ℹ️Webinar program and more about the speakers:
https://www2.helsinki.fi/en/news/data-science-news/hidata-webinar-on-bioinformatics
📲Channel: @Bioinformatics
📘 Free Ebook: Introduction to Biomedical Data Science
This ebook introduces methods, tools, and software for reproducibly managing, manipulating, analyzing, and visualizing large-scale biomedical data. Specifically, it introduces the R statistical computing environment and packages for manipulating and visualizing high-dimensional data, covers strategies for reproducible research, and culminates with analysis of data from a real RNA-seq experiment using R and Bioconductor packages.
⬇️ Download from here:
https://github.com/bioconnector/bims8382/raw/gh-pages/textbook.pdf
📲Channel: @Bioinformatics
This ebook introduces methods, tools, and software for reproducibly managing, manipulating, analyzing, and visualizing large-scale biomedical data. Specifically, it introduces the R statistical computing environment and packages for manipulating and visualizing high-dimensional data, covers strategies for reproducible research, and culminates with analysis of data from a real RNA-seq experiment using R and Bioconductor packages.
⬇️ Download from here:
https://github.com/bioconnector/bims8382/raw/gh-pages/textbook.pdf
📲Channel: @Bioinformatics
📚 Selected books/urls for bioinformatics/data science curriculum
From tommy weblog, A computational biologist working on (epi)genomics, single-cell transcriptomics
http://crazyhottommy.blogspot.com/2019/09/my-opinionated-selection-of-booksurls.html
📲Channel: @Bioinformatics
From tommy weblog, A computational biologist working on (epi)genomics, single-cell transcriptomics
http://crazyhottommy.blogspot.com/2019/09/my-opinionated-selection-of-booksurls.html
📲Channel: @Bioinformatics
🦴Machine learning Solutions for Osteoporosis – a Review
Osteoporosis and its clinical consequence, bone fracture, is a multifactorial disease that has been the object of extensive research. Recent advances in machine learning (ML) have enabled the field of artificial intelligence (AI) to make impressive breakthroughs in complex data environments where human capacity to identify high‐dimensional relationships is limited. The field of osteoporosis is one such domain, notwithstanding technical and clinical concerns regarding the application of ML methods. This qualitative review is intended to outline some of these concerns and to inform stakeholders interested in applying AI for improved management of osteoporosis.
✍️Study the paper here:
https://asbmr.onlinelibrary.wiley.com/doi/abs/10.1002/jbmr.4292
📲Channel: @Bioinformatics
Osteoporosis and its clinical consequence, bone fracture, is a multifactorial disease that has been the object of extensive research. Recent advances in machine learning (ML) have enabled the field of artificial intelligence (AI) to make impressive breakthroughs in complex data environments where human capacity to identify high‐dimensional relationships is limited. The field of osteoporosis is one such domain, notwithstanding technical and clinical concerns regarding the application of ML methods. This qualitative review is intended to outline some of these concerns and to inform stakeholders interested in applying AI for improved management of osteoporosis.
✍️Study the paper here:
https://asbmr.onlinelibrary.wiley.com/doi/abs/10.1002/jbmr.4292
📲Channel: @Bioinformatics
🌱 Gene transfer between plant and insect
https://www.nature.com/articles/d41586-021-00782-w
📲Channel: @Bioinformatics
https://www.nature.com/articles/d41586-021-00782-w
📲Channel: @Bioinformatics
Nature
First known gene transfer from plant to insect identified
Nature - Discovery that a whitefly uses a stolen plant gene to elude its host’s defences may offer a route to new pest-control strategies.
👨🏫Introduction to Bioinformatics and Computational Biology
Free course videos from Harvard University
Spring 2021
📑https://liulab-dfci.github.io/bioinfo-combio/
Contributors
♦️Xiaole Shirley Liu - Harvard University and Dana-Farber Cancer Institute
♦️Joshua Starmer - StatQuest
♦️Martin Hemberg - Sanger Institute
♦️Ting Wang - Washington University
♦️Feng Yue - Northwestern University
♦️Gad Getz - Harvard University and Broad Institute
📲Channel: @Bioinformatics
Free course videos from Harvard University
Spring 2021
📑https://liulab-dfci.github.io/bioinfo-combio/
Contributors
♦️Xiaole Shirley Liu - Harvard University and Dana-Farber Cancer Institute
♦️Joshua Starmer - StatQuest
♦️Martin Hemberg - Sanger Institute
♦️Ting Wang - Washington University
♦️Feng Yue - Northwestern University
♦️Gad Getz - Harvard University and Broad Institute
📲Channel: @Bioinformatics
✅ Ten Quick Tips for Deep Learning in Biology
https://benjamin-lee.github.io/deep-rules/manuscript.pdf
📲Channel: @Bioinformatics
https://benjamin-lee.github.io/deep-rules/manuscript.pdf
📲Channel: @Bioinformatics
📎 Applying NLP algorithms to the study of proteins
🗒New open access paper:
https://www.sciencedirect.com/science/article/pii/S2001037021000945
💥From research abstract:
Proteins, which can be represented as strings of amino-acid letters, are a natural fit to many NLP methods. We explore the conceptual similarities and differences between proteins and language, and review a range of protein-related tasks amenable to machine learning. We present methods for encoding the information of proteins as text and analyzing it with NLP methods, reviewing classic concepts such as bag-of-words, k-mers/n-grams and text search, as well as modern techniques such as word embedding, contextualized embedding, deep learning and neural language models. In particular, we focus on recent innovations such as masked language modeling, self-supervised learning and attention-based models. Finally, we discuss trends and challenges in the intersection of NLP and protein research.
📲Channel: @Bioinformatics
🗒New open access paper:
https://www.sciencedirect.com/science/article/pii/S2001037021000945
💥From research abstract:
Proteins, which can be represented as strings of amino-acid letters, are a natural fit to many NLP methods. We explore the conceptual similarities and differences between proteins and language, and review a range of protein-related tasks amenable to machine learning. We present methods for encoding the information of proteins as text and analyzing it with NLP methods, reviewing classic concepts such as bag-of-words, k-mers/n-grams and text search, as well as modern techniques such as word embedding, contextualized embedding, deep learning and neural language models. In particular, we focus on recent innovations such as masked language modeling, self-supervised learning and attention-based models. Finally, we discuss trends and challenges in the intersection of NLP and protein research.
📲Channel: @Bioinformatics
📕 Computational Genomics with R
2020-09-30 Online book from Altuna Akalin
https://compgenomr.github.io/book/
📲Channel: @Bioinformatics
2020-09-30 Online book from Altuna Akalin
https://compgenomr.github.io/book/
📲Channel: @Bioinformatics
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41%
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👨🏫 A guide to exploring genes and genomes with Ensembl
Free webinar from EMBL-EBI
This webinar is suitable to any researcher in life sciences who is interested in studying genes and genomes. No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.
🗓 Apr 14, 2021 03:30 PM in London
✍️ Register here
ℹ️ More information:
https://www.ebi.ac.uk/training/events/guide-exploring-genes-and-genomes-ensembl/#vf-tabs__section--tab1
📲Channel: @Bioinformatics
Free webinar from EMBL-EBI
This webinar is suitable to any researcher in life sciences who is interested in studying genes and genomes. No prior knowledge of bioinformatics is required, but an undergraduate level knowledge of biology would be useful.
🗓 Apr 14, 2021 03:30 PM in London
✍️ Register here
ℹ️ More information:
https://www.ebi.ac.uk/training/events/guide-exploring-genes-and-genomes-ensembl/#vf-tabs__section--tab1
📲Channel: @Bioinformatics
🏎 Copenhagen Bioinformatics Hackathon 2021
The event is 100% remote - so you and everybody else will be hacking from home
🗓 Friday 23rd April 18.00 CET to Sunday 25th April 14.00
Application Deadline: 10th of April
✍️ Register here
ℹ️ More information
📲Channel: @Bioinformatics
The event is 100% remote - so you and everybody else will be hacking from home
🗓 Friday 23rd April 18.00 CET to Sunday 25th April 14.00
Application Deadline: 10th of April
✍️ Register here
ℹ️ More information
📲Channel: @Bioinformatics
🧬Cancer May Be Driven by DNA Outside of Chromsomes
https://www.the-scientist.com/features/cancer-may-be-driven-by-dna-outside-of-chromosomes-68590
📲Channel: @Bioinformatics
https://www.the-scientist.com/features/cancer-may-be-driven-by-dna-outside-of-chromosomes-68590
📲Channel: @Bioinformatics
The Scientist Magazine®
Cancer May Be Driven by DNA Outside of Chromosomes
In the last decade, researchers have come to realize that tumors harbor bits of extrachromosomal DNA that can drive malignancy.
💉Scientists post the Moderna vaccine's sequence on GitHub
https://mashable.com/article/moderna-covid-19-vaccine-github-code/
📲Channel: @Bioinformatics
https://mashable.com/article/moderna-covid-19-vaccine-github-code/
📲Channel: @Bioinformatics
Mashable
Scientists figured out the Moderna COVID-19 vaccine's code and posted it on Github
No, this isn't going to result in bootleg vaccines.
💻 Developing and Implementing Cloud-Based Tutorials That Combine Bioinformatics Software, Interactive Coding, and Visualization Exercises for Distance Learning on Structural Bioinformatics
💥From paper abstract:
Following a cloud-based approach, we migrated the practical activities of a course on molecular modeling and simulation into the Google Colaboratory environment resulting in 12 tutorials that introduce students to topics such as phylogenetic analysis, molecular modeling, molecular docking, several flavors of molecular dynamics, and coevolutionary analysis. Each of these notebooks includes a brief introduction to the topic, software installation, execution of the required tools, and analysis of results, with each step properly described.
💥Download the paper from here:
https://pubs.acs.org/doi/10.1021/acs.jchemed.1c00022
💥All tutorials are freely available at:
https://github.com/pb3lab/ibm3202
📲Channel: @Bioinformatics
💥From paper abstract:
Following a cloud-based approach, we migrated the practical activities of a course on molecular modeling and simulation into the Google Colaboratory environment resulting in 12 tutorials that introduce students to topics such as phylogenetic analysis, molecular modeling, molecular docking, several flavors of molecular dynamics, and coevolutionary analysis. Each of these notebooks includes a brief introduction to the topic, software installation, execution of the required tools, and analysis of results, with each step properly described.
💥Download the paper from here:
https://pubs.acs.org/doi/10.1021/acs.jchemed.1c00022
💥All tutorials are freely available at:
https://github.com/pb3lab/ibm3202
📲Channel: @Bioinformatics
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👨🏫 Machine learning workshop; A full-fledged practical guide for beginners
✍️ Registration Link
www.zenitiq.com
🏅The workshop will be conducted by certified trainer and certificates will be provided to all the participants.
📆 17th and 18th April 2021
⏰ 2 - 5pm MYT (GMT +8)
💻ZOOM PLATFORM
📖Course content:
📌Introduction to machine learning using R Programming
📌Modelling using machine learning algorithms
📌Feature selection using machine learning
📌Interpretation of modelling and feature selection
📲Channel: @Bioinformatics
✍️ Registration Link
www.zenitiq.com
🏅The workshop will be conducted by certified trainer and certificates will be provided to all the participants.
📆 17th and 18th April 2021
⏰ 2 - 5pm MYT (GMT +8)
💻ZOOM PLATFORM
📖Course content:
📌Introduction to machine learning using R Programming
📌Modelling using machine learning algorithms
📌Feature selection using machine learning
📌Interpretation of modelling and feature selection
📲Channel: @Bioinformatics
👨🏫 Free Mathematical Biology Seminar
The Enigma Story: From Alan Turing & James Bond to BlackBerry & Quantum Encryption
🗓Monday, April 12, 2021
3 pm – Virtual
💻 Click to Join Zoom Meeting
Meeting ID: 991 2869 3119
Passcode: 533614
By:
Peter Berg
Professor in Mathematics & Physics, Chair
Department of Science
University of Alberta - Augustana Campus
📲Channel: @Bioinformatics
The Enigma Story: From Alan Turing & James Bond to BlackBerry & Quantum Encryption
🗓Monday, April 12, 2021
3 pm – Virtual
💻 Click to Join Zoom Meeting
Meeting ID: 991 2869 3119
Passcode: 533614
By:
Peter Berg
Professor in Mathematics & Physics, Chair
Department of Science
University of Alberta - Augustana Campus
📲Channel: @Bioinformatics
📑 Computational resources for identification of cancer biomarkers from omics data
Paper published in Briefings in Functional Genomics, 01 April 2021
⬇️ Download Link:
https://doi.org/10.1093/bfgp/elab021
📲Channel: @Bioinformatics
Paper published in Briefings in Functional Genomics, 01 April 2021
⬇️ Download Link:
https://doi.org/10.1093/bfgp/elab021
📲Channel: @Bioinformatics
🎓 Online MSc Bioinformatics
💥Flexible, 100% online study
⏰ Duration: 2.5 Years
🗓 Start Date: June 2021
✍️ More information: Click here
📲Channel: @Bioinformatics
💥Flexible, 100% online study
⏰ Duration: 2.5 Years
🗓 Start Date: June 2021
✍️ More information: Click here
📲Channel: @Bioinformatics
🧬Everything about RNA-Seq
🔗 https://rnaseq.uoregon.edu/
The purpose of this site is to provide a comprehensive discussion of each of the steps that are involved in performing RNA-seq, and to highlight the primary options that are available along with some guidance for choosing between various options. The primary content is topically organized according to the work-flow of a typical RNA-seq experiment.
📲Channel: @Bioinformatics
🔗 https://rnaseq.uoregon.edu/
The purpose of this site is to provide a comprehensive discussion of each of the steps that are involved in performing RNA-seq, and to highlight the primary options that are available along with some guidance for choosing between various options. The primary content is topically organized according to the work-flow of a typical RNA-seq experiment.
📲Channel: @Bioinformatics
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