International Workshop on Machine Learning Applications for R&D in Biotechnology

About Course

Held on 6th September to 12th September 2023 (7 to 8 pm)

Module 1: Introduction to Data Science in Biotechnology

  • Understanding Data Science in the Biotech Context
  • Overview of Prediction Algorithms in Biotechnology
  • Importance of Data Quality and Preprocessing
  • Hands-on: Data Preprocessing for Biotech Datasets

Module 2: Fundamentals of Machine Learning

  • Supervised vs. Unsupervised Learning in Biotech Applications
  • Key Machine Learning Concepts for Biotechnologists
  • Database Handling for Biotech Data: Challenges and Solutions
  • Introduction to File Formats and Conversions in Biotech Data

Module 3: Machine Learning Algorithms for Biotech Predictions

  • Regression Algorithms for Continuous Data Prediction
  • Classification Algorithms for Categorical Data Prediction
  • Feature Selection and Dimensionality Reduction in Biotech Data
  • Practical: Building a Predictive Model for a Biotech Case Study

Module 4: Applying Machine Learning in Cancer Genomics

  • Cancer Genomics: Introduction and Significance
  • Sequence Alignment Analysis in Cancer Genomics
  • Introduction to Machine Learning Tools for Sequence Analysis
  • Hands-on: Utilizing Machine Learning Software for Cancer Sequence Analysis

Module 5: Machine Learning in Cancer Genomics and Proteomics

  • Naive Bayes Algorithm: Theory and Application in Biotech
  • Naive Bayes for Cancer Genomics: Case Study and Examples
  • Naive Bayes in Proteomics: Analyzing Protein Data
  • Workshop Project: Implementing Naive Bayes for Biotech Data Analysis

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Course Content

Workshop on Machine Learning Applications for R&D in Biotechnology
Learn the most significant Skills for any Life Science or Biomedical discipline. Machine Learning and Data Science have become increasingly important in many scientific fields, including Biotechnology and Bioinformatics.

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