🧪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.
🌐 Study the paper
📲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
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👨🏫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
🇪🇸Region specific post
📣 BIOINFO CLUB NOVIEMBRE 2021 📣
Factores genéticos implicados en el agravamiento de la sepsis
🗓 16 de Noviembre
🕖 De 19h a 20:00h, CET
📚 Imparte:
👉 Tamara Hernández, PhD student (Universidad de La Laguna)
ℹ️ Registro + información:
buff.ly/3H0hciM
📲Channel: @Bioinformatics
📣 BIOINFO CLUB NOVIEMBRE 2021 📣
Factores genéticos implicados en el agravamiento de la sepsis
🗓 16 de Noviembre
🕖 De 19h a 20:00h, CET
📚 Imparte:
👉 Tamara Hernández, PhD student (Universidad de La Laguna)
ℹ️ Registro + información:
buff.ly/3H0hciM
📲Channel: @Bioinformatics
🧑🎓42 thesis noscripts with denoscriptions for MSc students of bioinformatics
💥from Wageningen University & Research
🖇 See details
📲Channel: @Bioinformatics
💥from Wageningen University & Research
🖇 See details
📲Channel: @Bioinformatics
👨🏻💻Bioinformatics Computing
🎞Fall 2021 Recorded lectures + Slides from Edwards Lab in Georgetown University
💥This course provides a hands-on introduction to programming for bioinformatics using the noscripting language Python. Students will build a portfolio of noscripts that automate common bioinformatics tasks, from reading and writing common bioinformatics file formats and accessing data in relational databases and web-based repositories, interfacing with external tools such as blast, and building web-based resources for use by interactive users or as web-services.
🕸 Course webpage
📲Channel: @Bioinformatics
🎞Fall 2021 Recorded lectures + Slides from Edwards Lab in Georgetown University
💥This course provides a hands-on introduction to programming for bioinformatics using the noscripting language Python. Students will build a portfolio of noscripts that automate common bioinformatics tasks, from reading and writing common bioinformatics file formats and accessing data in relational databases and web-based repositories, interfacing with external tools such as blast, and building web-based resources for use by interactive users or as web-services.
🕸 Course webpage
📲Channel: @Bioinformatics
🎞 Free webinar
*Application of Bioinformatics in current research*
🗓 Date: November 21 2021
🕐 Time: 5.00-6.00 PM (IST)
✍🏻 Registrations
📲Channel: @Bioinformatics
*Application of Bioinformatics in current research*
🗓 Date: November 21 2021
🕐 Time: 5.00-6.00 PM (IST)
✍🏻 Registrations
📲Channel: @Bioinformatics
📑Machine learning for biology with Python
💥Machine learning is programming by example. There are a couple of different categories of biological and medical problems that fall into the machine learning category. We will practically learn an easy case here using python.
▫️Part 1
▫️Part 2
▫️Part 3
📲Channel: @Bioinformatics
💥Machine learning is programming by example. There are a couple of different categories of biological and medical problems that fall into the machine learning category. We will practically learn an easy case here using python.
▫️Part 1
▫️Part 2
▫️Part 3
📲Channel: @Bioinformatics
❤1