PTU is offering M.Sc. (Bioinformatics) (MSCBI) in Distance Education mode. This article provides you the complete syllabus of M.Sc. (Bioinformatics) (MSCBI)
PTU Syllabus M.Sc. (Bioinformatics) (MSCBI) 2014
SEMESTER I
MSCBI-101: Bioinformatics- 1
• Computational analysis of protein sequence, structures and function. Sequence and structure
databases, visualization and modeling tools. Methods for pairwise alignment, discovery and
searching for remote homologous in protein sequence databases.
• Construction of profile Hidden Markov models, including sequence weighting and Dirichlet mixture
priors. Multiple alignment of protein sequences. The prediction of secondary structure by neural
networks, hidden Markov models, and other methods.
• Analysis of X-ray, NMR and mass spectrometry data. Models of protein structure. Protein threading
methods.
• Computational methods for structure-structure alignment and prediction of function from
structure. Construction of protein structure models by homology. Ab initio prediction of protein
structure. Molecular dynamics models of protein structure and folding.
SEMESTER I
MSCBI-102: Biochemistry-I
• A general overview for graduate and advanced undergraduate students in agricultural, biological,
chemical and nutritional sciences.
• Chemistry of amino acids, proteins, carbohydrates, lipids, vitamins and protein structure;
Enzymology; carbohydrate metabolism.
• Metabolism of carbohydrates, amino acids nucleotides and lipids; biosynthesis and molecular
relationships among DNA, RNA and proteins;
• Genetic code.
• Regulation of gene expression; selected topics in the molecular physiology of plants and animals.
SEMESTER I
MSCBI-103: Machine Learning
• Algorithmic models of learning. Design, analysis, implementation, and applications of learning
algorithms.
• Learning of concepts, classification rules, functions, relations, grammars, value functions, models,
skills, behaviors and programms. Agents that learn from observation, examples, instruction,
induction, imitation, deduction, reinforcement, and interaction.
• Computational learning theory. Data mining and knowledge discovery using artificial neural
networks, decision trees, Bayesian learning, association rules, genetic algorithms, dimensionality
reduction, feature selection, and visualization.
• Learning from heterogeneous, distributed, dynamic data and knowledge sources. Learning in multiagent
systems.
• Selected applications in automated knowledge acquisition, pattern recognition, programm
synthesis, bioinformatics, and interest-based information systems.
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SEMESTER I
MSCBI-104: Theory of Statistics and Genetic Statistics
• Point estimation including maximum likelihood estimation, Bayes estimators, Bayesian and minimax
optimality, unbiasedness, sufficiency, completeness, Basu's theorem.
• Convergence in probability, convergence in distribution, laws of large numbers, central limit
theorm.
• Confidence intervals, prediction intervals; Hypothesis testing, Neyman-Pearson Lemma, uniformly
most powerful tests, likelihood ratio tests.
• Bayesian interval estimation and tests. Nonparametric methods, bootstrap.
• Probability applied to genetic systems; random matin; selection, mutation and migration; theory of
in breeding; effects of finite population size; basic concepts in quantitative genetics; prediction of
progress from artificial selection.
• Sampling designs and experimental designs to obtain information from markers; detecting major
genes; linkage analysis and segregation analysis; finding alignments and similarities between DNA
sequences; constructing phylogenetic trees.
SEMESTER I
MSCBI-105: Communication and Soft Skills
UNIT I
Essentials of Grammar:
• Parts of Speech
• Punctuation
• Vocabulary Building
• Phonetics
UNIT II
Office Management:
• Types of Correspondence
• Receipt and Dispatch of Mail
• Filing Systems
• Classification of Mail.
• Role & Function of Correspondence
• MIS
• Managing Computer
UNIT III
Letter & Resume Writing:
• Types of Letters-Formal / Informal
• Importance and Function
• Drafting the Applications
• Elements of Structure
• Preparing the Resume
• Do’s & Don’ts of Resume
• Helpful Hints
UNIT IV
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
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Presentation Skills:
• Importance of Presentation Skills
• Capturing Data
• Voice & Picture Integration
• Guidelines to make Presentation Interesting
• Body Language
• Voice Modulation
• Audience Awareness
• Presentation Plan
• Visual Aids
• Forms of Layout
• Styles of Presentation.
UNIT V
Interview Preparation:
• Types of Interview
• Preparing for the Interviews
• Attending the Interview
• Interview Process
• Employers Expectations
• General Etiquette
• Dressing Sense
• Postures & Gestures
UNIT VI
Group Discussion & Presentation:
• Definition
• Process
• Guidelines
• Helpful Expressions
• Evaluation
(Note: Every student shall be given 15 minutes. of presentation time & 45 minutes of discussion
on his/ her presentation.)
The student will be evaluated on the basis of :
his / her presentation style
Feedback of Faculty & Students
General Etiquette
Proficiency in Letter Drafting / Interview Preparation
The paper is internal and at least 3 tests will be taken. Best 2 of 3 shall account for
final grades (70% Test & 30% Presentation)
SEMESTER I
MSCBI-106: Practical
Bioinformatics – 1 - 20 Marks
Biochemistry – 1 - 20 Marks
Machine Learning - 20Marks
Theory of Statistics and Genetic Statistics - 15 Marks
Internal Assessment: 25 Marks
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
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SEMESTER II
MSCBI-201: Bioinformatics- 2
• Genomics databases and analysis of high-through put genomics data sets including genomic DNA,
ESTs, SNPs, DNA micro array expression data, yeast 2-hybrid and other methods.
• BLAST and related sequence comparison methods.
• Pairwise alignment of biosequences by dynamic programming. Using Gibbs Sampling, expectationmaximinization,
and other statistical methods to discover common motifs in biosequences. Multiple
alignment and database search using motif models.
• Methods for constructing phylogenetic trees. Hidden Markov models for finding genes and other
genomic features.
• Discriminative methods for the analysis of bioinformatics data including generalized linear models,
neural networks and support vector machines.
• Methods for locating genes and predicting gene function, including introduction to linkage analysis
and disease association studies using SNPs.
• Methods for modeling the structure of DNA and RNA, including stochastic context-free grammars
and pseudo-energy minimization methods.
SEMESTER II
MSCBI-202: Biochemistry – 2
• Chemical composition of living matter. Chemical composition of amino acids, proteins,
carbohydrates and lipids.
• Enzymology and co-enzymes.
• Metabolism of carbohydrates and biological oxidation.
• Metabolism of lipids, aminoacids, and nucleotides and membrance biochemistry.
• Biosynthesis of DNA, RNA and proteins; gene regulation; (selected topics).
• Structure and properties of Reactivity Biomolecules.
• Physical Biochemistry.
• Selected topics in physical chemistry in the context of applications to problems in biology,
biochemistry and food sciences. Not acceptable for credit toward a major in biochemistry or
biophysics.
• Protein Chemistry-Physical Methods.
• Protein structure determination as a means of understanding biological function.
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
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SEMESTER II
MSCBI-203: Design and Analysis of Algorithms
• Basic techniques for design and analysis of efficient algorithms. Sorting, searching, graph
algorithms, computational geometry, string processing and NP-completeness. Design techniques
such as dynamic programming and the greedy method.
• Asymptotic, worstcase, average-case amortized analyses. Data structures including heaps, hash
tables binary search trees and red-black trees.
• Programming projects.
• A study of basic algorithm design and analysis techniques. Advanced data structures, amortized
analysis and randomized algorithms.
• Applications to sorting, graphs, and geometry.
• NP-completeness and approximation algorithms
SEMESTER II
MSCBI-204: Database Systems
• Introduction to database concepts.
• Data models.
• Algebraic, first order calculus based, and user oriented query languages.
• Data storage, access methods, query execution, and transaction management. Parallel and
distributed databases. Special purpose databases.
• Information integration using data warehouses, mediators, wrappers, and data mining.
• Oral and written reports.
SEMESTER II
MSCBI-205: Practical
Bioinformatics – 2 - 20 Marks
Biochemistry – 2 - 20 Marks
Design and Analysis of Algorithms - 15 Marks
Database Systems - 20 Marks
Internal Assessment: 25 Marks
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
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SEMESTER III
MSCBI-301: Introduction to Data Structure for Biologists
• An object-oriented approach to programming and data structures for biologic. Object-oriented
programming. Strings. Stacks. Queues. Recursion. Lists. Trees. Graphs. Sorting. Algorithm Analysis.
• The course is designed to provide the fundamentals of data structures and programming for biology
students that already have basic programming skills.
SEMESTER III
MSCBI-302: Bio-computing and Computational Biology
• Students will become familiar with use of arrange of programming skills useful for writing
bioinformatics software. They will gain experience of work in small groups and of linking together
different types of program to form a software package.
• The UNIX operating system; PERL programming; Web authoring; relational databases; middle ware;
Corba. Assessment -Demonstration of software resulting from a group programming project.
• Introduction to essential statistical and computational methods and tools in molecular biology
research. Emphasis will be on concepts and principles, combined with hands on (keyboard)
applications.
• Topics include : molecular databases, score-based sequence analysis, amino acid substitution
scoring matrices, query search problems, dynamic programming and other methods for pairwise
sequence alignment, motif identification, multiple sequence alignment, construction of
phylogenetic trees from sequence data, gene structure prediction, protein structure prediction,
and selected current research topics.
SEMESTER III
MSCBI-303: Software Engineering
• Introduction to the general principles of software engineering.
• Covers current and classical topics from both practical and theoretical viewpoints.
• Topics include software evolution, project management, software inspections, design methods,
requirements analysis and specification, software testing, maintenance, software implementation,
human interfaces, and software engineering experimentation.
SEMESTER III
MSCBI-304: Pharmacology
• Drug metabolism & Pharmacogenetics.
• Frontiers in Pharmacology
• Statistical methdos in Pharmacology
• Introduction to Research in Pharmacology.
• Introduction to Pharmacoinformatics
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
Paramedical Syllabus Manual : 142 / 144
SEMESTER III
MSCBI-305: Practical
Introduction to Data Structure for Biologists - 20 Marks
Biocomputing and Computational Biology - 20 Marks
Software Engineering - 20 Marks
Pharmacology - 15 Marks
Internal Assessment: 25 Marks
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
Paramedical Syllabus Manual : 143 / 144
SEMESTER IV
MSCBI-401: Introduction to Java and Introductory Combinatorics
To introduce students to a modern programming language and help them gain sufficient fluency to
undertake research projects with a programming component; to lay the foundations for more advanced
study of object-oriented languages.
Objectives -to understand the basic concepts of programming; to learn the syntax and semantics of
Java; to be able to use a program development environment; to become familiar with some
fundamental algorithms and data structures.
Variables; arithmetic; input and output; operators and control statements; functions; arrays and
pointers; structures and strings; dynamic memory allocation; object-oriented programing.
Practical : Students will be expected to work their way through a set of pogramming exercises designed
to demonstrate various aspects of Java and object-oriented programming.
Permutations, combinations, binomial coefficients, inclusion-exclusion principle, discrete probability,
classical probability. Additional topics selected from recurrence relations, generating functions,
random walks, and Markov chains.
SEMESTER IV
MSCBI-402: Basic Research Skills
Objectives : This module is designed to provide a general appreciation of workplace and
communication skills pertinent to the biological and medical sciences and an understanding of some of
the legal constraints and requirements of biological/medical research. Inter-personal and personal
transferable skills will be given particular emphasis in an effort to better equip the student for the
workplace, as well as interaction with staff and students while attending their Masters course.
Assessment - Written essary presenting a topic related to Bioinformatics to a non-specialist reader.
Talk at a Student Symposium presenting an area of Bioinformatics to the rest of the class and other
members of the school.
SEMESTER IV
MSCBI-403: Computational Techniques for Genome Assembly and Analysis
This course focuses on practical sequence assembly and comparison techniques. It has a special
emphasison efficient techniques for processing raw and finished DNA sequences at the genome level.
Those techniques are increasingly important, as complete sequences are becoming available for animal
and plant genomes. Algorithms and software for assembly and analysis of genomes. Global alignment,
local alignment, overlapping alignment, baded alignment, linear-spaco alignment, word hashing, DNAprotein
alignment, DNA-cDN Aalignment, comparisation of two sets of sequences, construction of
contigs, generation of consensus sequences.
PTU/DEP/Paramedical/September 2005/Detailed Syllabus
Paramedical Syllabus Manual : 144 / 144
SEMESTER IV
MSCBI-404: Proteomics
• Protein Sequence Comparison
• Principles of Protein Structure Prediction
• Protein Multiple Sequence Alignment
• Automatics Structural Classification of Proteins
• Protein Structural Comparison
• Geometric Hashing, Rigid and Flexible Matching
• Protein Folding
• Methods of resolving Protein 3D Structures
SEMESTER III
MSCBI-505: Practical
Introduction to Java and Introductory Combinatorics - 20 Marks
Basic Research Skills - 20 Marks
Computational Techniques for Genome Assembly and Analysis - 20 Marks
Proteomics - 15 Marks
Internal Assessment: 25 Marks
