Coding For Chemists - Exclusive Hands-on Training Program With 3 Months & 6 Months Project Work in Python, R, BioPython & CADD For Data Analysis

CODING FOR CHEMISTS - A Rasayanika Initiative

Become a CHEM-CODER

Calling All Aspiring Chemistry & Pharma Candidates to Join Our Hands-on Training Program in Python, Biopython, R & CADD, and how To Use Them in Research Data Analysis

+ Work On Real Time Projects For 3 Months of 6 Months

Learning to Code Is Your Key to Unlocking Boundless Potential in Your Career

Starts From 13th May 2024

Dive into the World of Coding - Join Today!

Welcome to the Coding For Chemist & Pharma Candidates Hands-on Training program
in Python, R, Bio Python, and CADD Biological Data Analysis! In the rapidly evolving field of chemistry, pharmaceuticals, and life sciences, data-driven approaches are becoming increasingly critical for research, analysis, and decision-making. This comprehensive 15-day Training is designed to equip aspiring chemists, pharmacists, researchers, and life science enthusiasts with the essential coding skills necessary to harness the power of data analysis and computational chemistry.

Course Details:

• Start Date: 13th May 2024
• Duration: 15 Days, 3 & 6 Months Project Work
• Mode: Online Via Zoom
• Timings: 6 PM to 7 PM

Eligibility:

B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm, M.Pharm, Chemistry, Life Sciences, Ph.D. and Post Doc Students are welcome, who want to learn coding.

Individuals with a strong interest in cheminformatics, pharmaceuticals, and a basic understanding of chemistry are encouraged to apply.

Why Chemistry & Pharma Candidates Must Know R, Python & BioPython, CADD:

• R and Python: R and Python are two of the most widely used programming languages in cheminformatics, pharmaceuticals, and biological data analysis. R is known for its powerful statistical analysis capabilities, while Python is versatile and popular for its simplicity. Knowing both equips you to work with a broad range of chemical and biological data effectively.

• BioPython: BioPython is a specialized library for biological data analysis, providing tools and libraries for sequence analysis, phylogenetics, structural biology, and more. It streamlines common biological data manipulation tasks.

• CADD (Computer-Aided Drug Design): CADD plays a crucial role in drug discovery and development. Understanding CADD techniques is invaluable for researchers involved in pharmacology and drug-related research in the life sciences.

Why Coding is Essential for Chemists & Pharma Candidates: Its Advantages:

In the era of big data, chemists and pharmaceutical candidates can significantly benefit from incorporating coding into their skill set. Here are some of the key advantages:

• Efficient Data Handling: With the immense volume of chemical and biological data generated daily, coding skills enable you to manage, process, and analyze data much more efficiently.

• Customized Analysis: Coding allows you to tailor your analytical tools to meet the specific needs of your research, providing a level of customization that pre-built software may not offer.

• Reproducibility: Coding ensures that your research is reproducible, transparent, and shareable with the scientific community, enhancing the credibility of your work.

• Automation: Repetitive tasks can be automated, saving time and reducing the risk of errors in data analysis.

• Interdisciplinary Collaboration: Coding skills enable better collaboration between chemists, biologists, computer scientists, and statisticians, fostering interdisciplinary research.

Instructor:

• Dr. Nilofer K Shaikh, PhD: With a strong background in big data analysis using computational approaches in cancer omics data, Ms. Nilofer K Shaikh brings a wealth of experience from MIT ADT University. Her expertise spans cancer research, drug design, molecular dynamics simulation, data mining, and various omics technologies. Proficient in Python, R, and computational methodologies, she has a deep understanding of genomics, metabolomics, proteomics, transcriptomics, pharmacogenomics, and AI for cancer treatment. Her skillset also includes machine learning, MySQL database management, and natural language processing (NLP).

• Dr. Prakrity Singh: A dedicated computational biologist, holds a Ph.D. and specializes in solving complex biological issues using advanced computational techniques. As an SRF at CSIR-Indian Institute of Toxicology Research, her research focuses on understanding atomic structures of persistent organic pollutants and their impact on biological systems. Dr. Singh has made significant contributions to drug discovery and toxicity projects, with her work published in peer-reviewed journals. Her commitment to advancing scientific understanding in environmental protection and human health underscores her pioneering role in computational biology, shaping its future in toxicology.

• Mr. Prodyot Banerjee: An accomplished professional in Computer-Aided Drug Designing, Bioinformatics Analysis, and Genomics, with extensive experience from esteemed institutions like CSIR-IGIB, CSIR-CLRI, IIT Madras, and Delhi Technological University. Holding an M.Tech in Bioinformatics from Delhi Technological University, Prodyot has excelled in research and development roles, presenting his work at prestigious venues like IIT Kharagpur. His research is published in respected journals such as IEEE and Frontiers in Pharmacology, with ongoing contributions. Prodyot's GATE 2019 qualification from IIT Madras underscores his commitment to academic excellence and professional growth. With a proven track record and insatiable thirst for knowledge, he is an invaluable asset in bioinformatics, genomics, and computer-aided drug design fields.

Training Curriculum

Week 1: Introduction to Biological Data Analysis

Day 1: Getting Started with Python and R

• Python vs. R for Biological Data Analysis
• Installing Python, R, and Required Libraries

Day 2: Data Import and Manipulation

• Working with Biological Data Formats
• Basic Data Manipulation with Python and R

Day 3: Data Visualization

• Introduction to Data Visualization
• Creating Basic Plots with Matplotlib (Python) and ggplot2 (R)

Day 4: Exploratory Data Analysis (EDA)

• Understanding Your Biological Data
• EDA Techniques in Python and R

Day 5: Introduction to Bio Python

• What is Bio Python?
• Basic Bio Python Functions for Sequence Analysis

Week 2: Molecular Data Analysis

Day 6: Sequence Alignment

• Introduction to Sequence Alignment
• Pairwise Sequence Alignment with Bio Python

Day 7: Multiple Sequence Alignment

• Multiple Sequence Alignment with Bio Python
• Sequence Alignment Tools and Techniques

Day 8: Phylogenetic Analysis

• Building Phylogenetic Trees
• Tree Visualization and Interpretation

Day 9: Sequence Feature Analysis

• Identifying and Annotating Sequence Features
• Sequence Motif Search with Bio Python

Day 10: Protein Structure Analysis

• Introduction to Protein Structure Analysis
• Using Bio Python for Protein Structure Data

Week 3: Clinical Data Analysis

Day 11: Clinical Data Preprocessing

• Cleaning and Organizing Clinical Data
• Handling Missing Data

Day 12: Survival Analysis

• Introduction to Survival Analysis
• Kaplan-Meier Estimator and Cox Proportional Hazards Model in R

Day 13: File Parsing and Data Retrieval

• Reading and Writing FASTA Files
• Parsing GenBank Files

Day 14: CADD data analysis using Python and BioPython

• Working with molecular structures and visualization for drug designing
• Analyzing drug bioactivity data to screen potential drug candidates

Day 15: Project and Presentation

• Apply your knowledge in a real research project.
• Showcase your skills and insights gained during the training.
• Present your findings and contributions to the field.

Project Work Opportunities

In addition to the 15-day training program, participants have the option to engage in real-time projects for 3 or 6 months. Below are the available project topics along with the respective project guides:

1. Gene Expression Analysis using Python - Project Guide: Dr. Nilofer Shaikh

2. Identification of drug-like properties, and molecular interaction analysis of phytochemicals against cancer targets - Project Guide: Dr. Prakrity Singh

3. To Identify Novel mutations in neurological disorders using AI/ML based Databases - Project Guide: Prodyot Banerjee

4. Model development for the screening of log P value using machine learning based algorithms - Project Guide: Dr. Prakrity Singh

5. Virtual screening of novel druggable compounds using AI/ML based Tools - Project Guide: Prodyot Banerjee

6. Principal component analysis-based unsupervised feature extraction applied to in-silico drug discovery - Project Guide: Dr. Prakrity Singh

7. Comparative Analysis of Data Mining Tools and Classification Techniques using WEKA in Medical Bioinformatics - Project Guide: Dr. Prakrity Singh

8. Pharmacokinetic/ Pharmacodynamic studies of the druggable compounds and identifying the pockets and cavities of protein - Project Guide: Prodyot Banerjee

9. Identification and screening of antiviral compounds in terms of their ADME/T properties - Project Guide: Dr. Prakrity Singh

10. To carry out multiple ligand docking studies using the screened druggable compounds and to present the docked complex as per publication standards using visualization tools - Project Guide: Prodyot Banerjee

11. Gene function prediction from DNA coding sequence using AI/ML classifiers and databases - Project Guide: Prodyot Banerjee

12. Feature selection and clustering of gene expression profiles using biological knowledge - Project Guide: Dr. Prakrity Singh

13. To design mutant protein structure model using AlphaFold and to identify the protein’s stability - Project Guide: Prodyot Banerjee

Why Attend This Training:

This training offers a unique opportunity for chemistry and pharmaceutical candidates to gain hands-on experience in coding and biological data analysis. By participating in this program, you will:

• Build In-Demand Skills: Learn the coding languages and tools that are in high demand in the life sciences and cheminformatics fields.

• Advance Your Career: Acquire skills that will make you more competitive in the job market and open up a wide range of career opportunities in academia, research, and industry.

• Work on Real Time Projects & Publish papers

• Practical Experience: Gain practical experience in coding and data analysis through real-world examples and projects.

• Networking: Connect with experts and peers in the field, building valuable connections for your future endeavors.

• Apply Knowledge: The program culminates in a project and presentation, allowing you to apply your newfound skills to real-life chemical and biological data analysis challenges.

Join us for this transformative journey into the world of biological data analysis. Let coding be your gateway to unraveling the mysteries of chemistry and pharmaceuticals and enhancing your impact in the field. Don't miss this opportunity to take your career to the next level. Register now and embark on this exciting educational journey with us!

Frequently asked questions on Coding For Chemist & Pharma Candidates Training

Are these going to be live sessions?

The Coding For Chemist & Pharma Candidates Hands-on Training will combine live interactive sessions and assignments. However, our expert will be available to guide you throughout the course.

What If I miss a session?

The recording of the sessions will be available for five days post-completion of the Training. So you can go back and refer to the recordings, but make sure you do not miss the live sessions and take maximum benefit from it.

Will I need to install any software?

The course does not require any additional software. However, any requirement arises, the instructor will inform it before the sessions.

How to get the hard copy certificate?

To avail of the hard copy certificate, the candidate should complete the assignments. Upon submission of the same, a hard copy certificate will be sent to your address.

Whom do I contact for any further queries or technical difficulties?

Having any trouble? Get in touch with our team. Click on that Chat thingy or write to us cst@biotecnika.org or info@biotecnika.org.