π¦ Recent omics-based computational methods for COVID-19 drug discovery and repurposing
π Study the paper
π²Channel: @Bioinformatics
π Study the paper
π²Channel: @Bioinformatics
π¬Free webinar
π§βπ» The Role of Genomic Epidemiology in COVID-19 Response
π Date:
Wednesday, 6 October, 2021
π Time:
17:00 β 18:30 pm EAT (GMT+3) / 7 am PST / 9 pm WIB (Jakarta)
βοΈ Registration
π²Channel: @Bioinformatics
π§βπ» The Role of Genomic Epidemiology in COVID-19 Response
π Date:
Wednesday, 6 October, 2021
π Time:
17:00 β 18:30 pm EAT (GMT+3) / 7 am PST / 9 pm WIB (Jakarta)
βοΈ Registration
π²Channel: @Bioinformatics
π’Free Symposium
π§βπ» Its time to do MORE with multiomics
π Date:
Tuesday, October 12, 2021 - Thursday, October 14, 2021
π Time:
9:00 AM-12:30 PM Pacific Time
π₯Symposium Agenda
βοΈ Registration
βΉοΈ More information
π²Channel: @Bioinformatics
π§βπ» Its time to do MORE with multiomics
π Date:
Tuesday, October 12, 2021 - Thursday, October 14, 2021
π Time:
9:00 AM-12:30 PM Pacific Time
π₯Symposium Agenda
βοΈ Registration
βΉοΈ More information
π²Channel: @Bioinformatics
πSimple and Straightforward High-Throughput Proteomics Analysis
π₯from teach me in 10 min series
πβπ¨ watch
π²Channel: @Bioinformatics
π₯from teach me in 10 min series
πβπ¨ watch
π²Channel: @Bioinformatics
π1
π Bioinformatics Algorithms
π₯2018 Edition
The bestselling textbook presents students with a dynamic, "active learning" approach to learning computational biology.
π First five chapters are freely available online at this stage
π₯ Lecture videos for chapters
β Chapters FAQ
π²Channel: @Bioinformatics
π₯2018 Edition
The bestselling textbook presents students with a dynamic, "active learning" approach to learning computational biology.
π First five chapters are freely available online at this stage
π₯ Lecture videos for chapters
β Chapters FAQ
π²Channel: @Bioinformatics
πMachine learning methods, databases and tools for drug combination prediction
π₯From abstract: The object of this study is to introduce and discuss the recent applications of ML methods and the widely used databases in drug combination prediction. In this study, we first describe the concept and controversy of synergism between drug combinations. Then, we investigate various publicly available data resources and tools for prediction tasks. Next, ML methods including classic ML and deep learning methods applied in drug combination prediction are introduced. Finally, we summarize the challenges to ML methods in prediction tasks and provide a discussion on future work.
π Study the paper
π²Channel: @Bioinformatics
π₯From abstract: The object of this study is to introduce and discuss the recent applications of ML methods and the widely used databases in drug combination prediction. In this study, we first describe the concept and controversy of synergism between drug combinations. Then, we investigate various publicly available data resources and tools for prediction tasks. Next, ML methods including classic ML and deep learning methods applied in drug combination prediction are introduced. Finally, we summarize the challenges to ML methods in prediction tasks and provide a discussion on future work.
π Study the paper
π²Channel: @Bioinformatics
πA review of bioinformatic pipeline frameworks
Abstract: High-throughput bioinformatic analyses increasingly rely on pipeline frameworks to process sequence and metadata. Modern implementations of these frameworks differ on three key dimensions: using an implicit or explicit syntax, using a configuration, convention or class-based design paradigm and offering a command line or workbench interface. Here I survey and compare the design philosophies of several current pipeline frameworks. I provide practical recommendations based on analysis requirements and the user base.
π Study the paper
π²Channel: @Bioinformatics
Abstract: High-throughput bioinformatic analyses increasingly rely on pipeline frameworks to process sequence and metadata. Modern implementations of these frameworks differ on three key dimensions: using an implicit or explicit syntax, using a configuration, convention or class-based design paradigm and offering a command line or workbench interface. Here I survey and compare the design philosophies of several current pipeline frameworks. I provide practical recommendations based on analysis requirements and the user base.
π Study the paper
π²Channel: @Bioinformatics
πRecent advances in biomedical literature mining
π₯The goal of this paper is to provide a review of the recent advances in BLM from biomedical informatics (BMI) and computer science (CS) communities and inspire new research directions.
π Study the paper
π²Channel: @Bioinformatics
π₯The goal of this paper is to provide a review of the recent advances in BLM from biomedical informatics (BMI) and computer science (CS) communities and inspire new research directions.
π Study the paper
π²Channel: @Bioinformatics
π¬Free virtual workshop
π§βπ» Exploring biological networks and its application in health and disease
π Date:
08 - 12 November 2021
π Time:
Theory : 13h (62%)
Practical : 8h (38%)
Total : 21h lectures + 2h Virtual Poster Sessions
πLocation: Virtually via Zoom
βΉοΈ More information
βοΈ Registration
π²Channel: @Bioinformatics
π§βπ» Exploring biological networks and its application in health and disease
π Date:
08 - 12 November 2021
π Time:
Theory : 13h (62%)
Practical : 8h (38%)
Total : 21h lectures + 2h Virtual Poster Sessions
πLocation: Virtually via Zoom
βΉοΈ More information
βοΈ Registration
π²Channel: @Bioinformatics
π§βπ» 1st International Student Biohackathon in Central Asia
π₯International Student Biohackathon from Nazarbayev University iGEM focused on solving natural science problems using IT. Our hackathon covers a wide spectrum of problems from data analysis to running simulations based on biological data, we welcome everyone to participate regardless of their specialization or skill level!
π Date: October 10-12
πFormat: Online, Team based
π―Team size: 2-4 people
βοΈ Registration
β«οΈDeadline: October 7
β«οΈIndividual | Team
β«οΈIndividual applications will be assigned to teams by us
πWinners will receive unique merchandise along with a cash prize!
βΉοΈ More info: http://code-on.info
π²Channel: @Bioinformatics
π₯International Student Biohackathon from Nazarbayev University iGEM focused on solving natural science problems using IT. Our hackathon covers a wide spectrum of problems from data analysis to running simulations based on biological data, we welcome everyone to participate regardless of their specialization or skill level!
π Date: October 10-12
πFormat: Online, Team based
π―Team size: 2-4 people
βοΈ Registration
β«οΈDeadline: October 7
β«οΈIndividual | Team
β«οΈIndividual applications will be assigned to teams by us
πWinners will receive unique merchandise along with a cash prize!
βΉοΈ More info: http://code-on.info
π²Channel: @Bioinformatics
π1
π‘New inspiring paper for
Identification of hub genes based on WGCNA
π Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis
π²Channel: @Bioinformatics
Identification of hub genes based on WGCNA
π Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis
π²Channel: @Bioinformatics
πTen simple rules for
Organizing a bioinformatics training course in low- and middle-income countries
π Study the paper
π²Channel: @Bioinformatics
Organizing a bioinformatics training course in low- and middle-income countries
π Study the paper
π²Channel: @Bioinformatics
πCytoscape tutorial:
π₯How to add gene expression data to an interaction network
π Watch
πDetails:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of the nodes to represent the changes in gene expression
5. Search for a specific node in the network and create a sub-network from all nodes that interact with this node
6. Change the layout of the network
7. Save the network as an image
8. Save the node or edge table as a .csv file
π²Channel: @Bioinformatics
π₯How to add gene expression data to an interaction network
π Watch
πDetails:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color of the nodes to represent the changes in gene expression
5. Search for a specific node in the network and create a sub-network from all nodes that interact with this node
6. Change the layout of the network
7. Save the network as an image
8. Save the node or edge table as a .csv file
π²Channel: @Bioinformatics
YouTube
Cytoscape tutorial: How to add gene expression data to an interaction network
Describes how to:
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color ofβ¦
1. Load an interaction network on cytoscape from a file (uses bioGRID)
2. Filter nodes by species and create a sub-network from filtered nodes
3. Add your gene expression data to the network in the form of a table
4. Change the color ofβ¦
π§βπ Position for MSc or PhD in computational biology, bioinformatics or computer science
π₯To apply, please send a motivation leer stating why you would like to join our lab, your CV, and the contact information (or letters of recommendation) of at least two referees to:
Dr. Simona Lodato (simona.lodato@hunimed.eu)
π²Channel: @Bioinformatics
π₯To apply, please send a motivation leer stating why you would like to join our lab, your CV, and the contact information (or letters of recommendation) of at least two referees to:
Dr. Simona Lodato (simona.lodato@hunimed.eu)
π²Channel: @Bioinformatics
πGene Identification Tools in Bioinformatics
π₯One of the most essential aspects of bioinformatics is gene prediction. Gene prediction involves locating regions of genomic DNA that encode genes (protein-coding genes). Gene prediction or gene identification is extremely important because it helps scientists to distinguish between coding and non-coding regions of a genome, explain genes in terms of their function, conduct research related to detection, treatment, and prevention of genetic disorder diseases, etc. Genes are identified broadly via two methods, i.e., a) similarity-based searches and b) Ab-initio prediction. These methods are briefly discussed and related tools introduced.
π Study
π²Channel: @Bioinformatics
π₯One of the most essential aspects of bioinformatics is gene prediction. Gene prediction involves locating regions of genomic DNA that encode genes (protein-coding genes). Gene prediction or gene identification is extremely important because it helps scientists to distinguish between coding and non-coding regions of a genome, explain genes in terms of their function, conduct research related to detection, treatment, and prevention of genetic disorder diseases, etc. Genes are identified broadly via two methods, i.e., a) similarity-based searches and b) Ab-initio prediction. These methods are briefly discussed and related tools introduced.
π Study
π²Channel: @Bioinformatics
π A guide to molecular interactions
π₯Free recorded webinar
π Outcomes:
β«οΈExplain what molecular interactions are
β«οΈDescribe what IntAct can be used for
β«οΈSearch for interaction data
π Watch
π²Channel: @Bioinformatics
π₯Free recorded webinar
π Outcomes:
β«οΈExplain what molecular interactions are
β«οΈDescribe what IntAct can be used for
β«οΈSearch for interaction data
π Watch
π²Channel: @Bioinformatics
Panopto
A guide to molecular interactions
Zoom Meeting ID: 96843688152
β’ Host: EMBL-EBI Webinars
β’ Meeting Start: 05/26/2021 @ 3:08 PM
β’ Recording Start: 05/26/2021 @ 3:29 PM
β’ Duration: 1 hr 5 mins
β’ Host: EMBL-EBI Webinars
β’ Meeting Start: 05/26/2021 @ 3:08 PM
β’ Recording Start: 05/26/2021 @ 3:29 PM
β’ Duration: 1 hr 5 mins
π§βπ»Using Web BLAST Effectively
π₯from NCBI Virtual Workshop Series
π Date:
2021-10-14 @ 01:00 PM to 2021-10-14 @ 02:30 PM ET
πLocation: Online Event
βοΈ Registration (Deadline: 2021-10-01)
βΉοΈ More information
π²Channel: @Bioinformatics
π₯from NCBI Virtual Workshop Series
π Date:
2021-10-14 @ 01:00 PM to 2021-10-14 @ 02:30 PM ET
πLocation: Online Event
βοΈ Registration (Deadline: 2021-10-01)
βΉοΈ More information
π²Channel: @Bioinformatics