🧑‍⚕️ Whole genome sequencing shows promise in routine treatment of blood cancers

A study by university doctors found that sequencing the genome of people with blood cancers is often better and even quicker than conventional tests and costs about the same. The study was published Wednesday in the New England Journal of Medicine, one of the most prestigious peer-reviewed medical journals.
“What we showed is that genome sequencing has reached a point that it is now practical, fast, economical, clinically feasible and accessible for the routine testing of patients,” said Dr. David Spencer, medical director of Washington University’s McDonnell Genome Institute Clinical Sequencing Lab.

https://medicine.wustl.edu/news/for-blood-cancers-whole-genome-sequencing-may-be-able-to-replace-standard-genetic-tests-that-guide-therapy/?_ga=2.42947427.71587469.1615559294-1696562336.1615559294

📲Channel: @Bioinformatics

🧑‍🏫 Workshop on Genome Annotation using Ensembl Genome Browser

⏱ 23, 24 and 25 March 2021 | 6:00 to 9:00 PM IST (+5:30 GMT)

📝 Register Here:
https://genespectrum.co.in/bioinformatics-training/ensembl_workshop/

📞 For more details contact on whatsapp/telegram : +91 7021386045

📲Channel: @Bioinformatics

👁 Researchers identify 50 additional genes for eye color

An international team of scientists has identified 50 more genes for eye color. “We knew of all these people whether they had brown, blue or any other color eyes. Computers searched their DNA for areas that have something to do with eye color. In this way, we found 61 genes associated with eye color, 50 of which were still unknown,” Dr. Manfred Kayser of the Erasmus University Medical Center Rotterdam, said in an article on the university’s website. Study the paper here:
https://advances.sciencemag.org/content/7/11/eabd1239

📲Channel: @Bioinformatics

📹 64 Short lecture videos on bioinformatics
from the Center for Computational Biology and bioinformatics
at Indiana University School of Medicine

https://www.youtube.com/playlist?list=PLusPIkuVew_75IRojlv8uOhoxI89CFbKD

📲Channel: @Bioinformatics

👷‍♂️ Full-time fully virtual Co-Op position
2021 Computational Biology, Bioinformatics

https://jobs.merck.com/us/en/job/MERCUSR105237ENUS/2021-Computational-Biology-Bioinformatics-Co-Op?utm_source=linkedin&utm_medium=phenom-feeds

📲Channel: @Bioinformatics

🧑‍🏫 Workshop from McGill University on Introduction to single cell analysis concepts

This workshop intends to introduce the basic concepts underlying single-cell data generation, processing, and analysis. We will introduce the current state-of-the-art technologies for molecular profiling at the single cell level. The goal is to help participants get familiar with existing tools and understand the differences between them. The main focus of the hands-on section will be an example of the typical analysis workflow of single-cell RNA sequencing data. It is strongly recommended to have previous coding experience and a basic understanding of bulk genomic analyses. See more details here:
https://www.mcgill.ca/channels/channels/event/introduction-single-cell-analysis-concepts-329688

⏱ March 29, 2021 | 1 PM- 5 PM

📝 Register here:
https://mcgill.zoom.us/meeting/register/tZUvfumsqTgpG9w0bZmqEcEWCm1CMi2CfrvD

📲Channel: @Bioinformatics

📉 Workflow overview of pathway analysis protocol for RNA-seq data

Input data of normalized differentially expressed genes lists for samples (Top) is subjected to Data Processing and Pathway Analysis steps to generate both ranked lists and nodal network maps of biological functions and pathways of interest (Bottom).

🗒Source Paper:
https://www.mdpi.com/2409-9279/4/1/21/htm

📲Channel: @Bioinformatics

🎞 NCBI Mastery: A Beginner's Guide to Bioinformatics
A complete and Up to Date NCBI Video Guide

🗒 Including tons of tools and databases of NCBI like:
mRNA Sequence Retrieval and Analysis, Gene Database, FASTA Format, Genbank Format, Genbank Database, RefSeq Database, ORF Finder, Genome Database, Genome Data Viewer, Genome Assembly, SNP Database (dbSNP), ...

📝 More information details:
https://www.udemy.com/course/ncbi-mastery-beginners-guide-to-bioinformatics

⏱ Lifetime Time Access

📲Channel: @Bioinformatics

🏛 Conference on Computational Biology and Bioinformatics

🗓 Event Date: April 15 - 17, 2021

💣 Deadline: March 31, 2021 (Registration/Abstracts)

🕸 Location: Virtual

✍️ Registration and more information:
https://lbrn.lsu.edu/conference-on-biology-and-bioinformatics.html

📲Channel: @Bioinformatics

👨‍🏫 Registration is open for three week Genome Informatics Workshop

✍️ Registration Link
https://decodelife.org

💲 Fees: Rupees 1000 For Indian Participant. / Dollar 20 (USA) for Foreign Participant.
We have kept nominal fees in order to ensure that only serious candidates participate.

💥Key Features :
▫️E- Certificate of participation
▫️Global Instructors
▫️Videos access for all sessions

📲Channel: @Bioinformatics

👨‍🏫 Free online Training course in single-cell spring school

🗓 Time: One week course starts on 4.04.2021

👄 Language: English

✍️ Registration (deadline: 31.03.2021):
https://forms.gle/H3zXb1ofaSvZ3bKg8

ℹ️More information:
https://genomics.org.ua/2021/03/training-course-in-single-cell-biology/

📲Channel: @Bioinformatics

💾 Using Big data (large, complex datasets) for diabetes research

https://www.healio.com/news/endocrinology/20210321/niddk-big-data-programs-help-to-enhance-share-new-research-in-diabetes

📲Channel: @Bioinformatics

📎 New Review Paper:
Incorporating Machine Learning into Established Bioinformatics Frameworks
https://www.mdpi.com/1422-0067/22/6/2903/htm

Here, authors review recently developed methods that incorporate machine learning with techniques from molecular evolution, protein structure analysis, systems biology, and disease genomics. They outline the challenges posed for machine learning, and, in particular, deep learning in biomedicine, and suggest unique opportunities for machine learning techniques integrated with established bioinformatics approaches to overcome some of these challenges

📲Channel: @Bioinformatics

👨‍🏫 Spring 2021 MIT course on
Computational Systems Biology: Deep Learning in Life Science
🎞 With lecture videos, slides and other course materials

https://mit6874.github.io/

This courses introduces foundations and state-of-the-art machine learning challenges in genomics and the life sciences more broadly. It introduces both deep learning and classical machine learning approaches to key problems, comparing and contrasting their power and limitations. It seeks to enable students to evaluate a wide variety of solutions to key problems we face in this rapidly developing field, and to execute on new enabling solutions that can have large impact. Students will program using Python 3 and TensorFlow 2 in Jupyter Notebooks, a nod to the importance of carefully documenting their work so it can be precisely reproduced by others.

📲Channel: @Bioinformatics

💣 Genomics and Bioweapons

https://www.military.com/daily-news/opinions/2021/03/23/will-genomics-become-next-arena-of-china-us-military-competition.html

📲Channel: @Bioinformatics

🧠 'Zombie' genes? Research shows some genes come to life in the brain after death

In the hours after we die, certain cells in the human brain are still active. Some cells even increase their activity and grow to gargantuan proportions, according to new research from the University of Illinois Chicago.
In a newly published study in the journal Scientific Reports, the UIC researchers analyzed gene expression in fresh brain tissue — which was collected during routine brain surgery — at multiple times after removal to simulate the post-mortem interval and death. They found that gene expression in some cells actually increased after death.

Study the paper here:
DOI: 10.1038/s41598-021-85801-6

📲Channel: @Bioinformatics

❓How to Become a Bioinformatician
We’ve got the lowdown on the training you’ll need to pursue this career path, and a handy list of resources to get you started on your learning.

✍️ Level: Elementary

https://bitesizebio.com/38236/how-to-become-a-bioinformatician/

📲Channel: @Bioinformatics

👩‍🎓Postdoctoral and PhD Positions in Medical Bioinformatics
Saez-Rodriguez group – Heidelberg University

💥Position Summary
Postdoctoral and PhD positions are open in the group of Julio Saez-Rodriguez at Heidelberg University. The positions are in the context of various national and international collaborations to study multi-omics data sets, including single-cell data, to develop and apply computational methods to better understand and treat cancer and kidney disease. This work builds on recent and ongoing work in our group, and you will join an international and interdisciplinary group of scientists.
Candidates interested in using bioinformatics, machine learning, and mathematical modeling to analyze big data to advance personalized medicine are encouraged to apply. You are expected to hold a degree in statistics, mathematics, physics, engineering or computer science, or a degree in biological science with substantial experience in computational and statistical work.
Candidates should email their CV (including names of three references) and a letter of interest to jobs.saez@bioquant.uni-heidelberg.de. The letter of interest has to be tailored to our group, mentioning projects or articles of our group that you find interesting, and explaining how you would fit here and in the topic mentioned above. Please also provide a pointer to a code repository if possible.
There is no strict deadline, but priority will be given to applications by April 8th 2020. The starting date is fairly flexible within 2021.

🕸 for more information visit
www.saezlab.org

📲Channel: @Bioinformatics

👨‍🏫 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 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

📚 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