Bioinformatics – Telegram
Bioinformatics
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Bioinformatics, Computational Biology & Systems Biology

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🎞 Free recorded webinar
💥Mastering Phylogenetic Tree Creation & Optimization💥

https://www.dnastar.com/mastering-phylogenetic-tree-creation-and-optimization-with-megalign-pro/

📲Channel: @Bioinformatics
📖 Network modeling methods for precision medicine

Abstract:We discuss in this survey several network modeling methods and their applicability to precision medicine. We review several network centrality methods and two systems controllability methods . We demonstrate their applicability to precision medicine on three multiple myeloma patient disease networks. Each network consists of protein-protein interactions built around a specific patient's mutated genes, around the targets of the drugs used in the standard of care in multiple myeloma, and around multiple myeloma-specific essential genes. For each network we demonstrate how the network methods we discuss can be used to identify personalized, targeted drug combinations uniquely suited to that patient.

https://arxiv.org/pdf/2104.09206.pdf

📲Channel: @Bioinformatics
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🤒 -😊 New atlas can help understand the relationship between healthy and breast cancer cells

Australian researchers have documented the diversity of cells in the human breast, explaining the relationship between healthy breast cells and breast cancer cells.
The research, which relied on expertise spanning from breast cancer biology through to bioinformatics, measured gene expression in single cells taken from healthy women and cancerous breast tissue, including tissue carrying a faulty BRCA1 gene. This enabled the researchers to create an 'RNA atlas' that details the different cells found in these tissues.
The atlas, which was described in EMBO Journal, will enable researchers to better understand the different cell types that constitute breast tissue and how these change during the development of cancer.

📑 Paper link:
https://www.embopress.org/doi/full/10.15252/embj.2020107333

📲Channel: @Bioinformatics
📘 Data Visualization with R - Online Book

R is an amazing platform for data analysis, capable of creating almost any type of graph. This book helps you create the most popular visualizations - from quick and dirty plots to publication-ready graphs. The text relies heavily on the ggplot2 package for graphics, but other approaches are covered as well.

🧑‍🏫 Read the book from here:
https://rkabacoff.github.io/datavis/

📲Channel: @Bioinformatics
🧬 Sample Bioinformatics Analyses for Hub Gene Identification

🖇 https://www.hindawi.com/journals/cmmm/2021/5548918/

📲Channel:
@Bioinformatics
🧫 An insilico method to predict genetics that underpin adverse drug reactions

https://www.sciencedirect.com/science/article/pii/S2215016119303516#fig0015

📲Channel: @Bioinformatics
📈 Current trend and development in bioinformatics research

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03874-y

📲Channel: @Bioinformatics
👨‍🏫 Two Days Hands on training on Cancer Genomics

🗓 Duration: 22 May and 23 May 2021
11 a.m. to 12:30 p.m. and 1 p.m. to 2:30 pm. (IST)
📍Location:
Virtual via Zoom
💻Software used: R studio
🧓Eligibility: Anyone from Life science or related fields.

✍️ Registration Link
https://forms.gle/r5PADzXaZG5RmqBr5

💲 Fees: Rs. 799 | 25 USD

🌐 Website: https://lifegenbio.com/

📲Channel: @Bioinformatics
🏢 ISCB-Africa ASBCB Bioinformatics Conference 2021
Online Event

💣 Deadline for abstract submission: April 19, 2021

🗓 Date: 7-10 June, 2021

🖇Website & more info.: https://www.iscb.org/iscbafrica2021

📲Channel: @Bioinformatics
📑 Network based Approach to Drug Discovery: A Mini Review

🖇 Paper link

📲Channel: @Bioinformatics
❗️7 Key points about big data in pandemics

The use of data has played a central role in the COVID-19 pandemic, but it should come as no surprise that researchers are already looking at ways to improve data acquisition, management, and access. EMBL’s most recent Science and Society seminar, ‘Harnessing Big Data to Monitor and Tackle Pandemics‘, featured a panel of three speakers who shared their experiences and conclusions about these topics.

🔗 https://www.miragenews.com/just-gist-big-data-and-pandemics-in-seven-key-563697/

📲Channel: @Bioinformatics
💥Network Analysis of Herbs Recommended for the Treatment of COVID-19

In this study, we aimed to identify the pattern and combination of herbs used in the formulae recommended for treating different stages of COVID-19 using a network analysis approach. A total of 142 herbal formulae comprising 416 herbs were analyzed. All possible herbal pairs were examined, and the top frequently used herbal pairs were identified for each disease stage. The herb Glycyrrhizae radix et rhizoma is only identified in one herb pair, even though this herb is identified as one of the herbs with high frequency of use for every disease stage. This study may provide new insights and ideas for clinical research in the future.

📑Study more: https://doi.org/10.2147/IDR.S305176

📲Channel: @Bioinformatics
🎬Introduction to Biological Network Analysis
👩‍🏫Mini Courses from Donna Slonim at Tufts University

Session
1: Network Basics and Properties
Session 2: From Graphs to Function
Session 3: Identifying Network Modules
Session 4: Network Alignment and Querying

📲Channel: @Bioinformatics
🧑‍🎨 Tasks, Techniques, and Tools for Genomic Data Visualization

https://onlinelibrary.wiley.com/doi/full/10.1111/cgf.13727

📲Channel: @Bioinformatics
💊Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach

🖇 https://onlinelibrary.wiley.com/doi/full/10.1002/adtp.202100055

A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported.

📲Channel: @Bioinformatics
🧑‍🏫Workshop RNA-Seq using high-performance computing

🌐https://hbctraining.github.io/Intro-to-rnaseq-hpc-salmon-flipped/schedule/links-to-lessons.html

💥Learning Objectives
▫️Understand the necessity for, and use of, the command line interface (bash) and HPC for analyzing high-throughput sequencing data.
▫️Understand best practices for designing an RNA-seq experiment and analysis the resulting data.

📲Channel: @Bioinformatics