An integrative workflow to analyze disease networks

https://link.springer.com/protocol/10.1007%2F978-1-4939-7456-6_12

Channel: @Bioinformatics

📕Teaching NCBI Resources Through Case Studies

Five examples for NCBI BLAST

Channel: @Bioinformatics

✴️Expedite the drug discovery by

Computational Drug Repositioning

Channel: @Bioinformatics

📚Programming for Bioscientists

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4896647/pdf/pcbi.1004867.pdf

Channel: @Bioinformatics

📓 A brief history of Bioinformatics till 2018 form an OXFORD journal
💥Learn and find the recent subdisciplines for the future of bioinformatics researches

https://www.researchgate.net/profile/Jeff_Gauthier/publication/326839021_A_Brief_History_of_Bioinformatics/links/5d6e7e83299bf16522f2c6f0/A-Brief-History-of-Bioinformatics.pdf

Channel: @Bioinformatics

COVID-19 (2019-nCoV) Data Repository
by Johns Hopkins CSSE

https://github.com/CSSEGISandData/COVID-19

Channel: @Bioinformatics

💥 Main challenges researchers face in analyzing data, and the solutions

https://peerj.com/articles/5553/?utm_source=TrendMD&utm_campaign=PeerJ_TrendMD_0&utm_medium=TrendMD

Channel: @Bioinformatics

Question and Answers to know Synthetic Biology more:

https://phys.org/news/2020-05-qa-synthetic-biology.html

Channel: @Bioinformatics

💥 The relationship between COVID-19 severity and genetic background

Channel: @Bioinformatics

📔Biopython Tutorial and Cookbook
(Last Update – 25 May 2020)

http://biopython.org/DIST/docs/tutorial/Tutorial.pdf

💥Includes:
- Introduction
- Quick Starts
- Sequence Objects
- Sequence I/O
- Sequence Alignment / Multiple Sequence Alignment
- BLAST
- Accessing NCBI's Entrez DBs
- Swiss-Prot and ExPASy
- PDB Module
- Population Genetics
- Phylogenetics
- Motif analysis
- Cluster analysis
- Supervised learning methods
- KEGG
- ...

Channel: @Bioinformatics

📕 An online introductory tutorial for
learning genomics
💥mostly on the Linux command-line

🏬 from Massey University

genomics.sschmeier.com

Channel: @Bioinformatics

⚜️ Learn RNA-Seq data analysis

https://galaxyproject.github.io/training-material/topics/trannoscriptomics/tutorials/ref-based/tutorial.html

Channel: @Bioinformatics

🇧🇷 BRAZILIAN SYMPOSIUM ON BIOINFORMATICS 2020
23-27 NOVEMBER 2020 - online meeting

http://bsb.sbc.org.br/2020

Channel: @Bioinformatics

💥 A good flowchart for RNASeq data analysis after preparing the expression matrix

Channel: @Bioinformatics

📑 Online tutorial
Molecular dynamic modeling
Simulations of proteins, lipids, and nucleic acids with GROMACS

http://www.mdtutorials.com/gmx/index.html

Channel: @Bioinformatics

🎞 Lecture and training videos from one of Bioinformatics channel members
💥Dr. Girinath Pillai
(Scientist working on drug discovery drug design and bioinformatics)

https://www.youtube.com/giribio

Channel: @Bioinformatics

Dear All

Drug Discovery Hackathon 2020
more details: https://innovateindia.mygov.in/ddh2020/

We are starting FREE massive training course every day (M-F) on fundamental concepts of drug discovery and development. 30-40 sessions per verticals (V1, V2, V3)
Every Saturdays there will Q&A session for 2-3hrs

V1 - Science behind drug discovery - 2:30pm-4:00pm
V2 - AI ML modelling, Statistics - 4:00pm - 5:30pm
V3 - Practical session on Open and Proprietary softwares for CADD, ADME, MD, etc. - 6:00pm - 7:30pm
More details on the sessions from tomorrow : http://www.neist.res.in/ddh2020/

Sessions will be streamed on MIC Youtube channel: https://www.youtube.com/channel/UC--MSNrR_zO4Zb5OvwjWF4A

I am happy to answer any queries. Thanks!

💥Simple paper (easy computation method) that can be generalized into any bipartite relationship in biology or medicine
from Cancer Informatics Journal

Computational Prediction of Probable Single Nucleotide Polymorphism-Cancer Relationships
https://journals.sagepub.com/doi/full/10.1177/1176935120942216

Channel: @Bioinformatics

🎬 Bioinformatics related Ted Talk

https://www.ted.com/talks/irina_kareva_math_can_help_uncover_cancer_s_secrets

Channel: @Bioinformatics

💻 Common generic workflow for a machine learning analysis of omics data

including steps to reduce the dimension of the data through feature selection or feature extraction, higher-level machine learning analysis for classifying omics data samples (a supervised analysis) or clustering the samples (an unsupervised analysis), and evaluation of the obtained machine learning models on external test data

Channel: @Bioinformatics