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Instructor Name

Dr. Omics (OP)

Category

Internships

Reviews

5 (1 Rating)

Course Requirements

  • Motivation to Learn: A strong desire to engage with and understand the material.
  • Basic Knowledge: Familiarity with biology and molecular biology concepts.
  • Interest in Technology: Eagerness to learn about the latest technologies in Next-Generation Sequencing (NGS).
  • Software: Free software will be utilized, so no additional software purchases are necessary.
  • Hardware: A laptop with a minimum of 4GB RAM and 100GB of hard disk space.

Course Description

  • Bioinformatics Fundamentals: Explore databases (NCBI, PubChem), tools (BLAST, Mega), and Linux basics.
  • Computer-Aided Drug Design (CADD): Introduction to drug discovery, chemical structure visualization, and molecular biology fundamentals.
  • Molecular Modeling Techniques: Hands-on practice with molecular visualization tools like PyMOL and Chimera.
  • Chemical Informatics and Virtual Screening: Utilize chemical databases for data mining and virtual screening.
  • Machine Learning in Drug Design: Basics of machine learning, data preprocessing, and application in drug-target interaction prediction.
  • Real-World Application: Collaborate on a research project, from designing to publication, gaining practical experience in CADD.
  • HR Sessions: Resume building, interview prep, career development.

Course Outcomes

  • Gain proficiency in bioinformatics tools and databases.
  • Understand the fundamentals of drug design and computational methods.
  • Develop skills in molecular modeling and chemical informatics.
  • Master machine learning techniques for drug design applications.
  • Apply acquired knowledge to real-world research projects, collaborating with industry professionals.
  • Enhance professional development with HR sessions.

Rules & Regulations

  • Attendance and Participation: Maintain a minimum of 75% attendance. Regular assessments and attendance contribute to performance evaluation.
  • Discipline: Maintain punctuality and respect in live classes. Engage actively and interact respectfully with instructors and peers.
  • Course Fee Payment: Pay course fees on time to avoid suspension or cancellation of access.
  • Assignments and Project: Complete assignments and projects sincerely and submit them on time.
  • Feedback and Communication: Maintain open communication with instructors and provide constructive feedback.
  • Certification: A certificate will be awarded upon course completion.
  • Paper Publication: eligibility requires a minimum 75% combined attendance and performance score.

Course Curriculum DOWNLOAD BROCHURE

1 21/10/24 day-01
59 Min


2 22/10/24 Day 2
1 Hour


3 23/10/24 Day 3
59 Min


4 24/10/24 Day 4
59 Min


5 25/10/24 Day 5
1 Hour


1 Overview of Bioinformatics (C429524)
52 Min


2 Pubmed Database(C429524)
55 Min


3 Genbank Assignment (C429524)
55 Min


4 Genbank Assignment part2 (C429524)
55 Min


5 Introduction UCSC genome browser (C429524)
55 Min


6 UCSC genome browser Exercise (C429524)
55 Min


7 PubChem Database (C429524)
55 Min


8 KEGG Database (C429524)
55 Min


9 Uniprot Database (C429524)
55 Min


10 PDB Database (C429524)
55 Min


11 Clinvar Database (C429524)
55 Min


12 Alignment tools-BLAST(online) (C429524)
55 Min


13 Standalone BLAST Setup and Exercises (C429524)
55 Min


14 Standalone BLAST Advanced Exercises (C429524)
55 Min


15 Multiple sequence Alignment(clustalW) (C429524)
55 Min


1 Overview of Linux and Installation (C429524)
50 Min


2 Basic File operations (C429524)
55 Min


3 File permissions and ownership (C429524)
55 Min


4 Basic linux commands (C429524)
55 Min


5 Linux text editors and tool installation (C429524)
55 Min


1 HR Session 1 (C429524)
55 Min


2 HR Session 2 (C429524)
55 Min


3 HR Session 3 (C429524)
55 Min


4 HR Session 4 (C429524)
55 Min


5 HR Session 5 (C429524)
55 Min


1 Introduction to Python (C429524)
44 Min


2 Data Types (C429524)
55 Min


3 String Handling (C429524)
55 Min


4 Control Structure(C429524)
55 Min


5 Data Structure(C429524)
55 Min


6 Function(C429524)
55 Min


7 File Handling(C429524)
55 Min


8 Data Manipulation(C429524)
55 Min


9 Data Visualization(C429524)
1 Hour


10 Biopython(C429524)
1 Hour


1 M4T1 = Introduction and Installation of R
59 Min


2 M4T2= Data Types in R
59 Min


3 M4T3= Data Structure
1 Hour


4 M4T4= File Handling
1 Hour


5 M4T5=Control Structure
1 Hour


6 M4T6 = Function
1 Hour


7 M4T7= Package Management
1 Hour


8 M4T8= Data Manipulation
59 Min


9 M4T9= Data Visualization
59 Min


10 M4T10= Statistical Analysis
59 Min


1 M6T1 =Introduction to Drug Discovery Process
1 Hour


2 M6T2=Role of Computational Methods
1 Hour


3 M6T3= Hands-on: Chemical Structure Visualization
1 Hour


4 M6T4= Biomolecules and Their Properties
1 Hour


5 M6T5= Structure of Proteins and Ligands
1 Hour


6 M6T6= Hands-on: Protein Structure Visualization
1 Hour


7 M7T7= Molecular Visualization Tools
1 Hour


8 M6T8= Molecular Mechanics and Dynamics Simulations
1 Hour


9 M6T9= Molecular Mechanics and Dynamics Simulations (continued)
1 Hour


10 M6T10= Chemical Databases and Data Mining
59 Min


11 M6T11= Ligand and Structure-Based Virtual Screening
1 Hour


12 M6T12= Hands-on: Chemical Data Exploration
59 Min


13 M6T13= Advanced Virtual Screening Techniques
1 Hour


14 M6T14= Virtual Screening using Autodock Vina
1 Hour


15 M6T15= Principles of Molecular Docking
1 Hour


16 M6T16= Scoring Functions in Docking
1 Hour


17 M6T17= Hands-on: Molecular Docking
1 Hour


18 M6T18= Introduction to Molecular Dynamics
59 Min


19 M6T19= Simulation Software (e.g., GROMACS)
1 Hour


20 M6T20= Hands-on: Analyzing MD Data
59 Min


21 M6T21= Chemoinformatics: Data Analysis and Visualization
1 Hour


22 M6T22= Protein-Ligand Interaction Analysis
1 Hour


23 M6T23= Hands-on Protein-Ligand Interaction Analysis
59 Min


24 M6T24= Pharmacophore Modeling and Applications
1 Hour


25 M6T25= Chemoinformatics: Data Analysis and Visualization (continued)
1 Hour


26 M6T26= Structure-Based Drug Design
1 Hour


27 M6T27= Ligand-Based Drug Design
1 Hour


28 M6T28= Hands-on Structure-Based and Ligand-Based Drug Design
59 Min


29 M6T29= ADMET in Drug Development
1 Hour


30 M6T30= Course Conclusion
1 Hour


1 M7T1= Basics of Machine Learning
59 Min


2 M7T2= Supervised, Unsupervised, and Reinforcement Learning
1 Hour


3 M7T3= Hands-on: Learn the Basics with scikit-learn Library in Python
59 Min


4 M7T4= Data Cleaning and Feature Selection
1 Hour


5 M7T5= Handling Molecular Data
1 Hour


6 M7T6= Hands-on: Use Pandas and NumPy for Data Preprocessing
1 Hour


7 M7T7= Regression and Classification Algorithms
58 Min


8 M7T8= Deep Learning in Drug Discovery
1 Hour


9 M7T9= Hands-on: Implement Machine Learning Models using scikit-learn
1 Hour


10 M7T10= Hands-on: Implement Machine Learning Models using TensorFlow/Keras
1 Hour


11 M7T11= Predicting Drug-Target Interactions
1 Hour


12 M7T12= QSAR Modeling
1 Hour


13 M7T13= Hands-on: Apply Machine Learning to Real Datasets with RDKit
59 Min


14 M7T14= Hands-on: Apply Machine Learning to Real Datasets with Cheminformatics
1 Hour


15 M7T15= Structure-Activity Relationship (SAR) Analysis
1 Hour


16 M7T16= Hands-on: Use RDKit for SAR Analysis
1 Hour


17 M7T17= De Novo Drug Design using ML
1 Hour


18 M7T18= Explore De Novo Design Tools
59 Min


19 M7T19= Advanced Machine Learning Techniques in Drug Design
1 Hour


20 M7T20= Integration of Omics Data in Drug Discovery
59 Min


21 M7T21= Clinical Trial Design and Data Analysis
1 Hour


22 M7T22= Ethical Considerations in Drug Design and Machine Learning
59 Min


23 M7T23= Real-World Applications
59 Min


24 M7T24= Q&A and discussion
59 Min


25 M7T25= Conclusion
59 Min


1. Draft
2. Draft 2

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CADD INTERNSHIP ( 6 MONTHS ) / C429524

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