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Program

Python for Biological Data Science: A Beginner’s Guide to Programming

Python , List, Tuple, Dictionary, Data Structures

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MODE
Online/ e-LMS
TYPE
Self Paced
LEVEL
Moderate
DURATION
4 Days (1Hour/ Day)
VIDEO LENGTH
4 Hours

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Summer

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Program Aim

The program “Python for Biological Data Science: A Beginner’s Guide to Programming” aims to introduce participants to the fundamentals of Python programming specifically tailored for analyzing biological data. By providing a comprehensive understanding of Python syntax, data structures, and libraries commonly used in bioinformatics, the program equips beginners with the essential skills needed to manipulate, visualize, and analyze biological datasets, fostering their proficiency in programming and empowering them to embark on careers or research endeavors in the rapidly evolving field of biological data science.

About Program

The program Python for Biological Data Science: A Beginner’s Guide to Programming is designed to provide newcomers to the field with a solid foundation in Python programming, tailored specifically for biological data analysis. Through a structured curriculum, participants are introduced to key programming concepts and techniques, including variables, control structures, functions, and object-oriented programming, with a focus on their application in the context of bioinformatics. Additionally, the program covers essential Python libraries and tools commonly used in biological data analysis, such as Biopython, NumPy, pandas, and matplotlib, enabling participants to perform tasks such as sequence manipulation, data visualization, statistical analysis, and machine learning. By the end of the program, participants emerge equipped with the skills and confidence needed to effectively utilize Python programming for exploring, processing, and interpreting biological data, positioning them for success in academic research, industry, or further study in the rapidly expanding field of biological data science.

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Program Objectives

  1. Install Python Basics: Guide participants through the installation process of Python and necessary packages.
  2. Python Data Types: Introduce numeric and string data types in Python, emphasizing their usage and manipulation.
  3. Python Data Structures: Explore list, tuple, and dictionary data structures in Python, providing examples relevant to biotechnology applications.
  4. Python Control Flow: Teach participants how to use conditional statements (if-else) and loops for DNA and protein sequence analysis.
  5. DNA Sequence Operations: Demonstrate how to generate complement and reverse complement sequences, calculate DNA composition, and determine melting temperature of primers.

Program Structure

  1. Python Basics Installation
  2. Python Data types – Numeric and String
  3. Python Data Structures – List, Tuple, Dictionary – with examples from Biotechnology
  4. Python control flow – if else and loops – DNA and Protein sequence analysis
  5. Generating complement and reverse complement of a DNA Sequence Program to calculate DNA composition and melting temperature of primer Program to find if a given DNA sequence has recognition sequence for a given restriction site

Participant’s Eligibility

  1. Biological Sciences Students: Undergraduate and graduate students majoring in biology, biochemistry, biotechnology, genetics, or related fields who wish to acquire programming skills for analyzing biological data.
  2. Researchers in Biology: Professionals working in research laboratories or academic institutions who seek to enhance their proficiency in Python programming specifically for biological data analysis.
  3. Bioinformatics Enthusiasts: Individuals interested in bioinformatics and computational biology who lack prior programming experience but wish to learn Python for analyzing biological data.
  4. Healthcare Professionals: Doctors, clinicians, or healthcare professionals interested in leveraging programming skills to explore biomedical datasets or research areas related to genetics, genomics, or personalized medicine.
  5. Educators: Teachers, instructors, or educators in biological sciences who wish to incorporate programming and bioinformatics into their curriculum or teaching methodologies.

Important Dates

Registration Ends

2023-02-12
Indian Standard Timing 10:00AM

Program Dates

2023-02-12 to 2023-02-15
Indian Standard Timing 11:00 AM ONWARDS

Program Outcomes

  1. Proficiency in installing Python and essential packages required for biotechnological applications.
  2. Mastery of Python data types, including numeric and string data, for effective data manipulation.
  3. Competency in utilizing Python data structures such as lists, tuples, and dictionaries for organizing and storing biotechnological data.
  4. Ability to apply Python control flow constructs (if-else statements and loops) for DNA and protein sequence analysis tasks.
  5. Skill in performing DNA sequence operations, including generating complement and reverse complement sequences, calculating DNA composition, and determining primer melting temperature.

Mentor Profile

Name: DR. VIPIN SINGH
Designation: Ph.D. – CCMB
Affiliation: Ph.D. – CCMB, Hyderabad, Post Doctoral Fellow – 2019-20, IBENS, Paris

Dr. Vipin Singh is a former Associate Professor in the University Institute of Biotechnology, Chandigarh University, Mohali, India. He received his Ph.D. Degree in Biotechnology from Centre for Cellular and Molecular Biology, Hyderabad and earned his postdoctoral from Institute of Biology, Ecole Normal Superior, IBENS – Paris. He has more than 11 years of research and teaching experience in Genome data analysis, Molecular biology, Bioinformatics. His Area of Expertise include Molecular Biology, rDNA Technology, Genetics, Genomics and Proteomics, Bioinformatics -NGS Data Analytics, PERL, R, Python, Awk, Biopython. To date, he has been the resource person for 10 Workshops, the author of 9 research articles published in peer reviewed international Journals etc.

Fee Structure

Ph.D. Scholar / Researcher

INR. 1599
USD. 40

Academician / Faculty

INR. 1999
USD. 50

Industry Professional

INR. 2499
USD. 75

Student

INR. 999
USD. 35

Standard Fee:           INR 11,998           USD 200

Discounted Fee:       INR 5999             USD 100

Certificate

Program Assessment

  1. Participant Engagement: Assess the level of participant engagement and active participation throughout the program, including attendance, completion of assignments, participation in discussions, and involvement in hands-on exercises and projects.
  2. Program Content: Evaluate the quality, relevance, and comprehensiveness of the program’s content, including the coverage of Python programming concepts, bioinformatics tools and libraries, and practical applications to biological data analysis.
  3. Instructor Effectiveness: Assess the effectiveness of instructors or facilitators in delivering course material, providing clear explanations, addressing participant questions and concerns, and fostering a supportive learning environment.
  4. Learning: Evaluate the effectiveness of hands-on learning opportunities, including programming exercises, coding assignments, and projects that allow participants to apply their programming skills to analyze biological datasets and solve bioinformatics problems.
  5. Assessment Methods: Review the variety and appropriateness of assessment methods used to evaluate participant learning and progress, such as quizzes, exams, coding assignments, peer evaluations, and project presentations.
  6. Participant Feedback: Gather feedback from participants through surveys, questionnaires, or interviews to assess their satisfaction with the program, including the quality of instruction, relevance of content, usefulness of resources, and overall learning experience.

Future Career Prospects

  1. Bioinformatics Software Developer: Develop software applications, pipelines, and tools for analyzing biological data using Python programming and bioinformatics libraries, contributing to open-source projects or working in software development teams.
  2. Clinical Informatician: Work in healthcare settings to integrate Python-based bioinformatics tools and technologies into clinical workflows, supporting evidence-based medicine, diagnostic decision support, and personalized patient care.
  3. Biotechnology Specialist: Apply Python programming skills in biotechnology companies to develop novel therapeutics, diagnostic tests, and research tools, leveraging biological data analysis techniques to drive innovation in the biotech industry.
  4. Academic Educator: Teach Python programming and bioinformatics courses at universities, colleges, or training programs, preparing the next generation of scientists and researchers for careers in computational biology and bioinformatics.
  5. Consultant or Freelancer: Provide consulting services or freelance work in bioinformatics, offering expertise in Python programming, data analysis, and bioinformatics tool development to research institutions, biotech companies, or healthcare organizations.
  6. Entrepreneurship: Start a bioinformatics startup or tech company focused on developing innovative solutions for biological data analysis, leveraging Python programming and machine learning techniques to address unmet needs in healthcare, agriculture, or environmental science.

Job Opportunities

  1. Data Scientist: Work in interdisciplinary teams to analyze and interpret biological data sets, using Python programming alongside data science techniques such as machine learning and data visualization.
  2. Genomic Data Analyst: Process and analyze genomic data using Python programming, identifying genetic variants, analyzing gene expression patterns, and interpreting genomic data for research or clinical applications.
  3. Computational Biologist: Combine expertise in biology and Python programming to develop computational models, conduct simulations, and analyze biological systems at a molecular level.
  4. Educator or Trainer: Teach Python programming and bioinformatics skills to students, researchers, or professionals in academic institutions, training programs, or workshops.
  5. Consultant: Provide consulting services in bioinformatics, offering expertise in Python programming, data analysis, and bioinformatics tool development to research institutions, biotech companies, or healthcare organizations.
  6. Freelancer: Work as a freelance bioinformatics consultant or developer, taking on projects related to biological data analysis, software development, or custom tool creation.

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