📑Bioinformatics core competencies for undergraduate life sciences education
From Paper Abstract: Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year...
🌐 Read the paper
📲Channel: @Bioinformatics
From Paper Abstract: Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year...
🌐 Read the paper
📲Channel: @Bioinformatics
2021_Differential_Expression_Analysis_of_RNA_Seq_Data_and_Co_expression.pdf
9.8 MB
📑Practical Differential Expression Analysis of RNA-Seq Data and Co-expression Networks
📲Channel: @Bioinformatics
📲Channel: @Bioinformatics
🎞 📔 Pathways and Network Analysis 2021
👨🏻💻3 days full workshop details
🌐 Workshop details
📲Channel: @Bioinformatics
👨🏻💻3 days full workshop details
🌐 Workshop details
📲Channel: @Bioinformatics
👷Job opportunity
👨🏫Eligibility: Master or PhD degree in Bioinformatics, Computational Biology or similar area.
📑Contract type: Pemanent contract
🕦Work Hours: Full time - 40h/week
📍Location: Strassen (Luxembourg)
🗓 Start date: immediate
ℹ️ More info and apply
📲Channel: @Bioinformatics
👨🏫Eligibility: Master or PhD degree in Bioinformatics, Computational Biology or similar area.
📑Contract type: Pemanent contract
🕦Work Hours: Full time - 40h/week
📍Location: Strassen (Luxembourg)
🗓 Start date: immediate
ℹ️ More info and apply
📲Channel: @Bioinformatics
💵 25 awarded funds across 30 U.S. research sites
💥NIH providing $185 million for research to advance understanding of how human genome functions
ℹ️ More information
📲Channel: @Bioinformatics
💥NIH providing $185 million for research to advance understanding of how human genome functions
ℹ️ More information
📲Channel: @Bioinformatics
📹Introduction to Weighted Gene Co-expression Network Analysis (WGCNA)
💥recorded webinar
🎖 Goals:
▫️Introduction and motivation for co-expression network analysis
▫️Basics of weighted gene co-expression network analysis
▫️Step-by-step guide to WGCNA using the WGCNA package in R.
🌐 Watch
📲Channel: @Bioinformatics
💥recorded webinar
🎖 Goals:
▫️Introduction and motivation for co-expression network analysis
▫️Basics of weighted gene co-expression network analysis
▫️Step-by-step guide to WGCNA using the WGCNA package in R.
🌐 Watch
📲Channel: @Bioinformatics
YouTube
Webinar #7 – Introduction to Weighted Gene Co-expression Network Analysis
Goals of this webinar (molecular networks):
Introduction and motivation for co-expression network analysis
Basics of weighted gene co-expression network analysis
Step-by-step guide to WGCNA using the wgcna package in R.
Background reading available at: h…
Introduction and motivation for co-expression network analysis
Basics of weighted gene co-expression network analysis
Step-by-step guide to WGCNA using the wgcna package in R.
Background reading available at: h…
📑 How helpful are the protein-protein interaction databases and which ones?
🖇 Study the paper
📲Channel: @Bioinformatics
🖇 Study the paper
📲Channel: @Bioinformatics
👍1
🎬How machine learning approaches can be tailored to making discoveries with biological data
🧑🏫Nine hours recorded workshop + Slides
💥ICML 2021 Workshop on Computational Biology
🎥 Watch
🌐 Workshop website
📲Channel: @Bioinformatics
🧑🏫Nine hours recorded workshop + Slides
💥ICML 2021 Workshop on Computational Biology
🎥 Watch
🌐 Workshop website
📲Channel: @Bioinformatics
💾Ten simple rules for writing a paper about scientific software
Abstract: Papers describing software are an important part of computational fields of scientific research, like bioinformatics. These “software papers” are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers, covering some of the different scenarios and publication types that might be encountered, and important questions from which all computational researchers would benefit by asking along the way.
🌐 Study the paper
📲Channel: @Bioinformatics
Abstract: Papers describing software are an important part of computational fields of scientific research, like bioinformatics. These “software papers” are unique in a number of ways, and they require special consideration to improve their impact on the scientific community and their efficacy at conveying important information. Here, we discuss 10 specific rules for writing software papers, covering some of the different scenarios and publication types that might be encountered, and important questions from which all computational researchers would benefit by asking along the way.
🌐 Study the paper
📲Channel: @Bioinformatics
🎬Free webinar
🧑💻Impact of SARS-CoV-2 Infection on Host Gene Expression
🗓 Date:
Thursday, September 23, 2021
🕚 Time:
2pm EDT (11am PDT / 1pm CDT) 60 min
✍️ Registration and more details
📲Channel: @Bioinformatics
🧑💻Impact of SARS-CoV-2 Infection on Host Gene Expression
🗓 Date:
Thursday, September 23, 2021
🕚 Time:
2pm EDT (11am PDT / 1pm CDT) 60 min
✍️ Registration and more details
📲Channel: @Bioinformatics
Xtalks
Impact of SARS-CoV-2 Infection on Host Gene Expression Across Multiple Tissues at Single Cell Resolution
Join this webinar to learn more about the alteration of host gene expression as a result of COVID-19 infection, and novel laboratory techniques designed to evaluate this at a single-cell resolution
🦠 Recent omics-based computational methods for COVID-19 drug discovery and repurposing
📑 Study the paper
📲Channel: @Bioinformatics
📑 Study the paper
📲Channel: @Bioinformatics
🎬Free webinar
🧑💻 The Role of Genomic Epidemiology in COVID-19 Response
🗓 Date:
Wednesday, 6 October, 2021
🕚 Time:
17:00 – 18:30 pm EAT (GMT+3) / 7 am PST / 9 pm WIB (Jakarta)
✍️ Registration
📲Channel: @Bioinformatics
🧑💻 The Role of Genomic Epidemiology in COVID-19 Response
🗓 Date:
Wednesday, 6 October, 2021
🕚 Time:
17:00 – 18:30 pm EAT (GMT+3) / 7 am PST / 9 pm WIB (Jakarta)
✍️ Registration
📲Channel: @Bioinformatics
🏢Free Symposium
🧑💻 Its time to do MORE with multiomics
🗓 Date:
Tuesday, October 12, 2021 - Thursday, October 14, 2021
🕚 Time:
9:00 AM-12:30 PM Pacific Time
🥇Symposium Agenda
✍️ Registration
ℹ️ More information
📲Channel: @Bioinformatics
🧑💻 Its time to do MORE with multiomics
🗓 Date:
Tuesday, October 12, 2021 - Thursday, October 14, 2021
🕚 Time:
9:00 AM-12:30 PM Pacific Time
🥇Symposium Agenda
✍️ Registration
ℹ️ More information
📲Channel: @Bioinformatics
🎞Simple and Straightforward High-Throughput Proteomics Analysis
💥from teach me in 10 min series
👁🗨 watch
📲Channel: @Bioinformatics
💥from teach me in 10 min series
👁🗨 watch
📲Channel: @Bioinformatics
👍1
📖 Bioinformatics Algorithms
💥2018 Edition
The bestselling textbook presents students with a dynamic, "active learning" approach to learning computational biology.
🌐 First five chapters are freely available online at this stage
🎥 Lecture videos for chapters
❔ Chapters FAQ
📲Channel: @Bioinformatics
💥2018 Edition
The bestselling textbook presents students with a dynamic, "active learning" approach to learning computational biology.
🌐 First five chapters are freely available online at this stage
🎥 Lecture videos for chapters
❔ Chapters FAQ
📲Channel: @Bioinformatics
📑Machine learning methods, databases and tools for drug combination prediction
💥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.
🌐 Study the paper
📲Channel: @Bioinformatics
💥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.
🌐 Study the paper
📲Channel: @Bioinformatics
📑A 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.
🌐 Study the paper
📲Channel: @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.
🌐 Study the paper
📲Channel: @Bioinformatics