👨‍🏫 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

📑 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

🎓 Online MSc 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

🧾 Computational network biology: Data, models, and
applications

A review paper from Physics Reports (IF=25.79)
https://doc.rero.ch/record/328505/files/zha_cnb.pdf

Biological entities are involved in intricate and complex interactions, in which uncovering the biological information from the network concepts are of great significance. Benefiting from the advances of network science and high-throughput biomedical technologies, studying the biological systems from network biology has attracted much attention in recent years, and networks have long been central to our understanding of biological systems, in the form of linkage maps among genotypes, phenotypes, and the corresponding environmental factors. In this review, we summarize the recent developments of computational network biology, first introducing various types of biological networks and network structural properties. We then review the network-based approaches, ranging from some network metrics to the complicated machine-learning methods, and emphasize how to use these algorithms to gain new biological insights. Furthermore, we highlight the application in neuroscience, human disease, and drug developments from the perspectives of network science, and we discuss some major challenges and future directions. We hope that this review will draw increasing interdisciplinary attention from physicists, computer scientists, and biologists.

📲Channel: @Bioinformatics

🦷 Antibody May Be Able to Regenerate Missing Teeth

🗞 News detail
https://www.kyoto-u.ac.jp/en/research-news/2021-03-31

📎 Publication information:
https://doi.org/10.1126/sciadv.abf1798

📲Channel: @Bioinformatics

🎞 Introduction to Machine Learning on Biomedical Data
▫️Free recorded Online Course
▫️Video+Required files

The course will begin with a very brief overview of the mathematical foundations of ML, specifically linear regression, logistic regression, and multilayer perceptrons. Applying these models to the well-studied dataset of hand written digits, MNIST, we’ll gain first-hand experience with model selection, training and validation. We will then introduce several abstractions from...
🖇 Course link

📲Channel: @Bioinformatics

🔬 Can one mRNA molecule be a template for multiple proteins in eukaryotes?

📹 https://phys.org/news/2021-02-video-green-algae-reveals-mrna.html

🗒Research link:
DOI: 10.1073/pnas.2017714118

📲Channel: @Bioinformatics

🧑‍🔬Systematic review of computational methods for predicting long noncoding RNAs
New paper from Briefings in Functional Genomics journal

🔗 https://doi.org/10.1093/bfgp/elab016

🗒From Abstract:
Long non-coding RNAs are a type of RNA, defined as being transcripts with lengths exceeding 200 nucleotides that are not translated into protein. In recent years, many computational methods have been developed to predict lncRNAs from transcripts, but there is no systematic review on these computational methods. In this review, authors introduce databases and features involved in the development of computational prediction models, and subsequently summarize existing state-of-the-art computational methods, including methods based on binary classifiers, deep learning and ensemble learning. However, a user-friendly way of employing existing state-of-the-art computational methods is in demand. Therefore, they develop a Python package ezLncPred, which provides a pragmatic command line implementation to utilize nine state-of-the-art lncRNA prediction methods. Finally, we discuss challenges of lncRNA prediction and future directions.

📲Channel: @Bioinformatics

👨‍🏫 Microbial Community Analysis Workshop
🆓Free and Virtual

🗓 May 18-27, 2021

💥Topics:
The workshop will cover best practices in bioinformatics analysis of amplicon-based microbial community data – using a 16S rRNA data set. Participants will learn to retrieve sequence data from the NCBI Sequence Read Archive (SRA), and will then use a BASH command-line environment on the Biomix computational cluster to perform sequence analysis. R will be used to perform downstream analysis and visualization of those data. Compositional statistical methods will be introduced and used throughout.

✍️ Register here
Seats are limited

ℹ️ More information:
https://bioinformatics.udel.edu/core/mcaw-2021/

📲Channel: @Bioinformatics

👨‍🏫 Vacancy
Tenure track 'Group leader translational tumor bioinformatics'

✅Tasks:
-Development of innovative technologies and bioinformatics for tumor diagnostics in close collaboration with laboratory specialists.
-Development of a research line in tumor bioinformatics.
-Academic supervision of bioinformaticians responsible for the implementation of innovative tumor diagnostics.
-Development of research collaborations with related research groups

ℹ️ Click here for More information

📲Channel: @Bioinformatics

🖥 Fantastic databases and where to find them: Web applications for researchers in a rush

🔗 https://www.scielo.br/scielo.php?pid=S1415-47572021000300801&script=sci_arttext

from Abstract
Here, we present an overview of human databases with web applications. The databases and tools allow the search of biological sequences, genes and genomes, gene expression patterns, epigenetic variation, protein-protein interactions, variant frequency, regulatory elements, and comparative analysis between human and model organisms. The goal is to provide an opportunity for exploring large datasets and analyzing the data for users with little or no programming skills. Public user-friendly web-based databases facilitate data mining and the search for information applicable to healthcare professionals. To show the databases at work, we present a case study using ACE2 as example of a gene to be investigated. The analysis and the complete list of databases is available in the paper.

📲Channel: @Bioinformatics

👶 Human placentas routinely consist of a quilt of different genotypes, and this strange heterogeneity may actually play a role in protecting the fetus from genetic harm

🖇https://www.quantamagazine.org/new-genomic-study-of-placenta-finds-deep-links-to-cancer-20210408

📑 Main research link

📲Channel: @Bioinformatics

Free Online Book for
📖Biomedical Data Science

🖇http://genomicsclass.github.io/book/

Channel: @Bioinformatics

🧑‍🏫*NGS Data Analysis Workshop*
Learn the most demanded skill in Bioinformatics without the need to code!!

⏱ *When :* 19 - 22 April | 6:30 to 8:30 PM IST

💵 *Fee :* Rs 1000 for Indian Nationals | USD 20 for Foreign Nationals

✅ All sessions will be conducted on Zoom
✅ Recording for each session will be shared with the participants
✅ E-Certificate will be provided to all the participants

ℹ️ Click here to know more and register

📲Channel: @Bioinformatics

🤒 Finding Cancer causing genes without mutation signature!

https://www.news-medical.net/news/20210413/New-algorithm-can-predict-which-genes-cause-cancer.aspx

📲Channel: @Bioinformatics

🏥 Building the learning ecosystem of health:
from data tracking to preventive medicine

https://www.youtube.com/watch?v=0oHGSeC25Pk

share your ideas at the ELIXIR Innovation and SME Forum, organized on 13 September 2021 as part of the BC2 Basel Computational Biology Conference.

⏳ Abstract submission deadline: 16 April

ℹ️ More information: https://www.bc2.ch/elixir-forum​

📲Channel: @Bioinformatics

😷A novel, quick, and easy system for genetic analysis of SARS-CoV-2

https://phys.org/news/2021-04-quick-easy-genetic-analysis-sars-cov-.html

📲 Channel: @Bioinformatics

💽 Sharing biological data: why, when, and how

https://febs.onlinelibrary.wiley.com/doi/10.1002/1873-3468.14067

💥Here, you can see good practices to make your biological data publicly accessible and usable, generally and for several specific kinds of data.

📲 Channel: @Bioinformatics

📘 Data Analysis and Visualization in R

These online lessons below were designed for those interested in working with genomics data in R. This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day (~ 6 hours). They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, how to calculate summary statistics from a data frame, and a brief introduction to plotting. The last lesson demonstrates how to work with databases directly from R

🔗https://datacarpentry.org/R-genomics

📲Channel: @Bioinformatics

🗞 Biden Administration Announces $1.7 Billion Investment for Genomics and Bioinformatics to Fight COVID-19 Variants

https://www.whitehouse.gov/briefing-room/statements-releases/2021/04/16/fact-sheet-biden-administration-announces-1-7-billion-investment-to-fight-covid-19-variants/

📲 Channel: @Bioinformatics