πPersonal Health Records: A Systematic Literature Review
πJournal: Journal of Medical Internet Research (I.F.=7.076)
πPublish year: 2017
π Study the paper
π²Channel: @Bioinformatics
#review #phr
πJournal: Journal of Medical Internet Research (I.F.=7.076)
πPublish year: 2017
π Study the paper
π²Channel: @Bioinformatics
#review #phr
π2
πTutorial series for visualizing and interpreting omic data
π Go to website
π²Channel: @Bioinformatics
#visualization #omic
π Go to website
π²Channel: @Bioinformatics
#visualization #omic
π11β€5
πFeature selection methods and genomic big data: a systematic review
πJournal: Journal of Big Data (I.F.=10.835)
πPublish year: 2019
π Study the paper
π²Channel: @Bioinformatics
#review #genomic #feature_selection
πJournal: Journal of Big Data (I.F.=10.835)
πPublish year: 2019
π Study the paper
π²Channel: @Bioinformatics
#review #genomic #feature_selection
π7
π An Introduction to Applied Bioinformatics
π₯Free online book with python examples
π Study the book
π²Channel: @Bioinformatics
#book #python
π₯Free online book with python examples
π Study the book
π²Channel: @Bioinformatics
#book #python
π13π₯1
πImpact of computational approaches in the fight against COVID-19: an AI guided review of 17000 studies
πJournal: Briefings in Bioinformatics (I.F.=13.994)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #covid-19
πJournal: Briefings in Bioinformatics (I.F.=13.994)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #covid-19
π2
πInterpretation of differential gene expression results of RNA-seq data: review and integration
πJournal: Briefings in Bioinformatics (I.F.=13.994)
πPublish year: 2019
π₯Abstract:
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.
π Study the paper
π²Channel: @Bioinformatics
#review #DEG
πJournal: Briefings in Bioinformatics (I.F.=13.994)
πPublish year: 2019
π₯Abstract:
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.
π Study the paper
π²Channel: @Bioinformatics
#review #DEG
π11
πAccelerating Drug Discovery with Machine Learning and AI
π₯Recorded Seminar
π½ Watch
π²Channel: @Bioinformatics
#video #drug #ai
π₯Recorded Seminar
π½ Watch
π²Channel: @Bioinformatics
#video #drug #ai
YouTube
Olexandr Isayev - Accelerating Drug Discovery with Machine Learning and AI
Presented on 2/4/2021
Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition, and computer vision. In this talk, we will provide an overview of the latest developments of machineβ¦
Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition, and computer vision. In this talk, we will provide an overview of the latest developments of machineβ¦
π5
πComputational drug repurposing based on electronic health records: a scoping review
πJournal: npj Digital Medicine (I.F.=15.357)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #drug #reproposing
πJournal: npj Digital Medicine (I.F.=15.357)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #drug #reproposing
π2
We are delighted to inform our
Two days Virtual Hands-on Training Workshop on "Membrane Protein Simulations using CHARMM-GUIβ πWorkshop Features:
- The workshop focuses on membrane Protein Simulations using CHARMM-GUI.
- Hands-on training and examples will be provided based on GROMACS software.
- The post Workshop Assessment Free Merit Seats will be given upon strict evolutions.
- Certifications will be provided for all the participants.
π₯Trainers
Trained by highly skilled trainers
π©βπMs. Hemavathy Nagarajan, India
π¨βπ»Dr. Shiv Bharadwaj, Prague Czech Republic
πFour different Modules to be covered
π₯Number Of Seats?
- 10 Post Workshop Assessment Free-Merit seats
- 30 Paid Seats (25 Euros / 2000 βΉ)
πFor More Info & π¨βπ»Register
https://www.nyberman.com/merit-workshops
π’«««««««
Channel @llbschool
Forum @letslearnbioinformatics
π²Channel: @Bioinformatics
π6β€2π1
π A comprehensive review of artificial intelligence and network based approaches to drug repurposing in Covid-19
πJournal: Biomedicine & Pharmacotherapy (I.F.=7.419)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #ai #reproposing #covid19
πJournal: Biomedicine & Pharmacotherapy (I.F.=7.419)
πPublish year: 2022
π Study the paper
π²Channel: @Bioinformatics
#review #ai #reproposing #covid19
π7
πA 10-step guide to party conversation for bioinformaticians
πJournal: Genome Biology (I.F.=17.906)
π Study the paper
π²Channel: @Bioinformatics
πJournal: Genome Biology (I.F.=17.906)
π Study the paper
π²Channel: @Bioinformatics
π3
πAlgorithmic complexity in computational biology: basics, challenges and limitations
π Study the paper
π²Channel: @Bioinformatics
#complexity
π Study the paper
π²Channel: @Bioinformatics
#complexity
π3β€1
πHealthcare data analysis and visualization using Power BI
π₯Recorded Seminar
π½ Watch
π²Channel: @Bioinformatics
#video #medical #Power_bi #visualization
π₯Recorded Seminar
π½ Watch
π²Channel: @Bioinformatics
#video #medical #Power_bi #visualization
YouTube
Analyzing Healthcare with Power BI
Check Out Our Power BI Blog - http://blog.pragmaticworks.com/topic/power-bi In this session, youβll see how to empower your users with self-service BI with healthcare-specific data. Youβll see how to use Power Map to and public data to determine where yourβ¦
π3π2π1
Forwarded from Network Analysis Resources & Updates
πBiological network analysis with deep learning
πJournal:Briefings in Bioinformatics (I.F=13.994)
πPublish year: 2021
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Biological #deeplearning
πJournal:Briefings in Bioinformatics (I.F=13.994)
πPublish year: 2021
π Study paper
π±Channel: @ComplexNetworkAnalysis
#paper #Biological #deeplearning
π6β€1
π An introduction to the R programming language for Bioinformatics students
π₯From University of Michigan Computational Medicine and Bioinformatics
π½ Part 1
π½ Part 2
π²Channel: @Bioinformatics
#video #r
π₯From University of Michigan Computational Medicine and Bioinformatics
π½ Part 1
π½ Part 2
π²Channel: @Bioinformatics
#video #r
YouTube
An introduction to the R programming language for Bioinformatics students - Part 1/2
π14β€10
πInsights Into Organizing Events in Bioinformatics: From In-Person to the Online World
πJournal: Frontiers in Bioinformatics
πPublish year: 2021
π Study the paper
π²Channel: @Bioinformatics
#online #in_person #workshop
πJournal: Frontiers in Bioinformatics
πPublish year: 2021
π Study the paper
π²Channel: @Bioinformatics
#online #in_person #workshop
π2
π¨βπ» Postdoc position of Computational Biology
at Humanitas Research Hospital
π²Channel: @Bioinformatics
#postdoc
at Humanitas Research Hospital
π²Channel: @Bioinformatics
#postdoc
π3
πRecent advances in network-based methods for disease gene prediction
πJournal:Briefings in Bioinformatics (I.F=13.994)
πPublish year: 2021
π Study paper
π²Channel: @Bioinformatics
#survey #gene #disease #prediction
πJournal:Briefings in Bioinformatics (I.F=13.994)
πPublish year: 2021
π Study paper
π²Channel: @Bioinformatics
#survey #gene #disease #prediction
π2