🎞 Free webinar
*Multi-Omics approach to infectious diseases: Current status and perspectives*
🗓 Date: October 23 2021
🕐 Time: 5.00 - 6.00 PM (IST)
✍🏻 Registrations
📲Channel: @Bioinformatics
*Multi-Omics approach to infectious diseases: Current status and perspectives*
🗓 Date: October 23 2021
🕐 Time: 5.00 - 6.00 PM (IST)
✍🏻 Registrations
📲Channel: @Bioinformatics
📊Visual Analytics of Genomic and Cancer Data: A Systematic Review
💥From abstract: ... This article provides a comprehensive systematic review and discussion on the tools, methods, and trends for visual analytics of cancer-related genomic data. We reviewed methods for genomic data visualisation including traditional approaches such as scatter plots, heatmaps, coordinates, and networks, as well as emerging technologies using AI and VR. We also demonstrate the development of genomic data visualisation tools over time and analyse the evolution of visualising genomic data...
🖇 Study the paper
📲Channel: @Bioinformatics
💥From abstract: ... This article provides a comprehensive systematic review and discussion on the tools, methods, and trends for visual analytics of cancer-related genomic data. We reviewed methods for genomic data visualisation including traditional approaches such as scatter plots, heatmaps, coordinates, and networks, as well as emerging technologies using AI and VR. We also demonstrate the development of genomic data visualisation tools over time and analyse the evolution of visualising genomic data...
🖇 Study the paper
📲Channel: @Bioinformatics
📚Programming for Biology
💥Online course with full materials
👉🏻 Website: http://programmingforbiology.org
🖇 Associate Github including all course materials
📲Channel: @Bioinformatics
💥Online course with full materials
👉🏻 Website: http://programmingforbiology.org
🖇 Associate Github including all course materials
📲Channel: @Bioinformatics
👍1
📃Representation Learning for Networks in Biology and Medicine: Advancements, Challenges, and Opportunities
🌐 Study the paper
📲Channel: @Bioinformatics
🌐 Study the paper
📲Channel: @Bioinformatics
🎞 Free webinar
Fundamentals of Next Generation Sequencing: A Sneak Peek into Genomics Lab
🗓 Date: 28 October 2021
🕐 Time: 11:00 AM
✍🏻 Registrations
📲Channel: @Bioinformatics
Fundamentals of Next Generation Sequencing: A Sneak Peek into Genomics Lab
🗓 Date: 28 October 2021
🕐 Time: 11:00 AM
✍🏻 Registrations
📲Channel: @Bioinformatics
👍1
🏢 5th International Symposium on Bioinformatics (InSyB) 2021
🗓 Date: December 15-17, 2021
📍Location: Virtually in Turkey with Bezmialem Vakıf University
✍️Registration and submissions are FREE!
💣 Abstract submission deadline: 15.11.2021
🖇Website: https://insyb2021.bezmialem.edu.tr/
📲Channel: @Bioinformatics
🗓 Date: December 15-17, 2021
📍Location: Virtually in Turkey with Bezmialem Vakıf University
✍️Registration and submissions are FREE!
💣 Abstract submission deadline: 15.11.2021
🖇Website: https://insyb2021.bezmialem.edu.tr/
📲Channel: @Bioinformatics
🧪Machine Learning in Enzyme Engineering
Abstract: Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have been increasingly applied to find patterns in data that help predict protein structures, improve enzyme stability, solubility, and function, predict substrate specificity, and guide rational protein design. In this Perspective, we analyze the state of the art in databases and methods used for training and validating predictors in enzyme engineering. We discuss current limitations and challenges which the community is facing and recent advancements in experimental and theoretical methods that have the potential to address those challenges. We also present our view on possible future directions for developing the applications to the design of efficient biocatalysts.
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📲Channel: @Bioinformatics
Abstract: Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have been increasingly applied to find patterns in data that help predict protein structures, improve enzyme stability, solubility, and function, predict substrate specificity, and guide rational protein design. In this Perspective, we analyze the state of the art in databases and methods used for training and validating predictors in enzyme engineering. We discuss current limitations and challenges which the community is facing and recent advancements in experimental and theoretical methods that have the potential to address those challenges. We also present our view on possible future directions for developing the applications to the design of efficient biocatalysts.
🌐 Study the paper
📲Channel: @Bioinformatics
👍1
👨🏫Introduction to Biomedical Data Science and Health Informatics
💥Yale University Full archive July 2020
Join us for an introduction to basic biomedical data science knowledge and health informatics skills. This course is targeted for beginners in informatics. No previous experience is required.
🌐 Go to online course
📲Channel: @Bioinformatics
💥Yale University Full archive July 2020
Join us for an introduction to basic biomedical data science knowledge and health informatics skills. This course is targeted for beginners in informatics. No previous experience is required.
🌐 Go to online course
📲Channel: @Bioinformatics
📹 Introduction to Metagenomics
▫️What is Metagenomics?
▫️What kind of questions can Metagenomics be used to answer?
▫️Is Metagenomics right for me?
▫️...
🖇 Watch
📲Channel: @Bioinformatics
▫️What is Metagenomics?
▫️What kind of questions can Metagenomics be used to answer?
▫️Is Metagenomics right for me?
▫️...
🖇 Watch
📲Channel: @Bioinformatics
📘 Illumina’s Ebook
High impact discovery through gene expression and regulation research
💥Learn more about methods to link genotype to phenotype
⬇️ Download the ebook
📲Channel: @Bioinformatics
High impact discovery through gene expression and regulation research
💥Learn more about methods to link genotype to phenotype
⬇️ Download the ebook
📲Channel: @Bioinformatics