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This course is designed to introduce biologists to the fundamentals of programming using Python. It covers the basics of Python programming, including data types, variables, control flow, functions, and file handling. Additionally, the course focuses on specific applications of Python in biology, such as data analysis, visualization, and bioinformatics.
Isha Gupta
Intermediate
Recorded
English
Certificate Provided
Time 7:00 to 8:00 PM IST
Last date 04 November
This course is designed to introduce biologists to the fundamentals of programming using Python. It covers the basics of Python programming, including data types, variables, control flow, functions, and file handling. Additionally, the course focuses on specific applications of Python in biology, such as data analysis, visualization, and bioinformatics.
Installation and setup of Python and an Integrated Development Environment (IDE) – Basic Python syntax and data types (numbers, strings, lists, dictionaries) – Writing and executing simple Python scripts
Reading and writing files (e.g., text files, CSV files) – Parsing data from files and extracting relevant information – Basic data manipulation using Python libraries (e.g., NumPy, Pandas)
Introduction to data visualization with Python (e.g., Matplotlib, Seaborn) – Creating simple plots (e.g., scatter plots, bar plots, line plots) – Customizing plots and adding labels, titles, and legends
Conditional statements (if-else) and loops (for, while) – Writing and using functions to modularize code – Best practices for writing efficient and readable code
Introduction to common biological data formats (FASTA, FASTQ, BED, etc.) – Overview of Python libraries for bioinformatics (e.g., Biopython, pysam) – Reading and processing biological data using relevant libraries
Sequence manipulation and analysis using Biopython – Sequence alignment and comparison – Calculating sequence properties (e.g., GC content, molecular weight)
Exploratory data analysis of biological datasets – Statistical analysis using Python libraries (e.g., SciPy, Statsmodels) – Hypothesis testing and visualization of results
Introduction to biological databases (e.g., GenBank, UniProt) – Retrieving data from databases using Python libraries (e.g., Biopython) – Parsing and analyzing retrieved data
Extracting relevant information from text using regular expressions – Text processing techniques for biological data (e.g., searching, pattern matching) – Natural Language Processing (NLP) basics for biological text analysis
Introduction to machine learning concepts – Supervised and unsupervised learning algorithms – Applying machine learning to biological datasets using Python libraries (e.g., scikit-learn)
Introduction to genomic and transcriptomic data analysis – Genome assembly and annotation using Python – Differential gene expression analysis using Python libraries (e.g., DESeq2)
Introduction to proteomic and metabolomic data analysis – Analyzing mass spectrometry data using Python libraries (e.g., Pyteomics) – Data preprocessing and statistical analysis
Introduction to network theory and its application in biology – Network construction and visualization using Python libraries (e.g., NetworkX) – Analyzing biological networks and identifying key nodes
Integrating multiple biological datasets for analysis – Visualization of integrated data using Python libraries (e.g., Plotly, Cytoscape) – Creating interactive visualizations for publication or presentations
Work on a small project applying Python to a specific biological problem – Review and consolidate the concepts learned throughout the 15 days – Discuss further resources and avenues for expanding Python skills in biology
Isha Gupta, an accomplished Bioinformatics faculty from Aligarh. Holds B.Tech and M.Tech degrees in Bioinformatics. Passionate about genomics and proteomics, with expertise in diverse bioinformatics projects. Dedicated to fostering student growth in the field.
I learned how to use python for data retrieval, analysis and many more things.
I got a chance to know about application of python in life sciences
I learnBiopython and data analysis
I learned one of the main programne
Session Joining link will be send to your register email on the day of session start you can join session by clicking joining link.
All Session are evening sessions time of session is between 7:00 to 8:00 PM IST.
Please read refund policy in refund policy section page.
No, any short Prerequisites knowledge you required to join the course.
