🔬 Exploring the computational methods for protein-ligand binding site prediction

✍️ Level: Advanced

Identifying the residues participating in these interactions not only provides biological insights for protein function studies but also has great significance for drug discoveries. In this review, authors introduce the research background of predicting protein–ligand binding sites and then classify the methods into four categories, namely, 3D structure-based, template similarity-based, traditional machine learning-based and deep learning-based methods.

https://www.sciencedirect.com/science/article/pii/S2001037019304465

📲Channel: @Bioinformatics

👦 Using machine learning to identify blood biomarkers for early diagnosis of autism

✍️ Level: Advanced

https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0246581

The more significantly affected the child is, the higher or lower than normal the blood biomarker is. Ideally, there will be a day when a child is identified using blood biomarkers as being at risk for developing ASD and therapies can be started immediately. That would help the child develop skills to optimize their communication and learning.

📲Channel: @Bioinformatics

💊 A new survey research of computational methods for drug-target interaction (DTI) prediction and related datasets

✍️ Level: Advanced

https://academic.oup.com/bib/article/22/1/247/5681786

The task of predicting the interactions between drugs and targets plays a key role in the process of drug discovery. In this article, authors describe the data required for the task of DTI prediction followed by a comprehensive catalog consisting of machine learning methods and databases, proposed and utilized to predict DTIs. The advantages and disadvantages of each set of methods are also discussed. Lastly, the challenges in prediction of DTI using machine learning approaches are highlighted and they conclude by shedding some lights on important future research directions.

📲Channel: @Bioinformatics

👨‍💻 Getting Started in Gene Expression Microarray Analysis

✍️ Level: Intermediate

Gene expression microarrays provide a snapshot of all the trannoscriptional activity in a biological sample. Unlike most traditional molecular biology tools, microarrays facilitate the discovery of totally novel and unexpected functional roles of genes. The power of these tools has been applied to a range of applications, including discovering novel disease subtypes, developing new diagnostic tools, and identifying underlying mechanisms of disease or drug response. However, this technology necessarily produces a large amount of data, challenging us to interpret it by exploiting modern computational and statistical tools. In this brief review, we aim to indicate the major issues involved in microarray analysis and provide a useful starting point for new microarray users.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000543

📲Channel: @Bioinformatics

💪 Computational Biology Boundaries

https://www.youtube.com/watch?v=eyFGZjiqLGg

📲Channel: @Bioinformatics

🧬 Sequencing Key Molecules in Just Minutes Instead of Years

https://scitechdaily.com/sequencing-key-molecules-in-just-minutes-instead-of-years/

📲Channel: @Bioinformatics

⚙ Nvidia and Harvard develop AI tool that speeds up genome analysis

https://venturebeat.com/2021/03/08/nvidia-and-harvard-develop-ai-tool-that-speeds-up-genome-analysis/

📲Channel: @Bioinformatics

🧑‍🏫 New research trends for metabolic network reconstruction

⏱ Time: 14-Mar-2021 / 19:00
🕸https://vc.sharif.edu/ch/soal

📲Channel: @Bioinformatics

🧑‍⚕️ 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