Update README.md

Author: prince26121991

README.md

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-# Biomedical-Data-Science
+# Biomedical-Data-Science
+This is a graduate-level course covering the fundamentals of transparent and reproducible bioinformatics, targeted towards biomedical students.
+
+Lab01.ipynb:
+Introduces basic Unix commands commonly used in bioinformatics workflows.
+Covers commands like ls, cd, and file manipulation in a Unix environment.
+
+Lab02.ipynb:
+Focuses on Unix scripting to automate tasks in bioinformatics.
+Demonstrates how to create simple scripts using bash for handling repetitive tasks.
+
+Lab03.ipynb:
+Introduces Python programming for bioinformatics applications.
+Covers basic syntax, data types, and control structures relevant to biological data analysis.
+
+Lab04.ipynb:
+Provides a setup guide and initial steps for using bioinformatics tools.
+Guides users through configuring their environment for data analysis.
+
+Lab05.ipynb:
+Continues with setting up the computational environment for bioinformatics workflows.
+Covers additional configuration steps and essential bioinformatics software.
+
+Lab06.ipynb:
+Further explores bioinformatics tools and environment setup for analysis.
+Introduces key tools and libraries used in data handling and analysis.
+
+Lab07.ipynb:
+Introduces Git and GitHub for version control in bioinformatics projects.
+Guides users through repository creation, committing changes, and collaborating on code.
+
+Lab08.ipynb:
+Explores the use of R in bioinformatics through Google Colaboratory.
+Introduces basic R syntax and data manipulation techniques in a cloud environment.
+
+Lab09.ipynb:
+Introduces the use of Salmon for transcript quantification in RNA-seq data.
+Demonstrates how to align reads and interpret output files for gene expression analysis.
+
+Lab10.ipynb:
+Guides users through working with a reference genome and sequence data.
+Demonstrates file manipulation using commands like head and visualization of genomic data.
+
+Lab11.ipynb:
+Covers the setup of Miniconda and Mamba for managing bioinformatics environments.
+Introduces the use of Mamba for faster package management and environment handling.