FORMAT FOR COURSE CURRICULUM 
                            Annexure ‘CD – 01’ 
     
       Course Title: Python for Biologist                                                           L    T   P/   SW/FW      TOTAL 
                                                                                                             S               CREDIT 
       Course Code: BIOF206                    Units: 04                                                                     UNITS 
                                                                                                     2   0   2       2           4 
       Course Objectives: 
                                                                                                    
       The course will enable students to apply Python for bioinformatics applications. The course will also enable the students to apply concepts of object oriented 
       programming and its modules. The course will enable students to analyze data using Python. 
     
       Pre-requisites: Basic knowledge about computer programming. 
     
        Course Learning Outcomes (CLO): on completion of the course student will be able to  
             •  Acquire programming skills in core Python and to develop the skills of designing Graphical User Interfaces.  
             •  Demonstrate a clear understanding  to utilize Python with reference to bioinformatics 
             •  Evaluate various  techniques using Python 
             •  Apply various methods  of Python language viz. Tkinter , Matploatlib and numpy with reference of Bioinformatics 
             •  Memorize and run the basic commands of bio python. 
             •  Analyze the bioinformatics data using python and bio python. 
                   
        
        
        
        
        
        
        
        
        
        
        
            Course Contents/Syllabus- Theory: 
                                                                                                                                                                                                                                                        Weightag
                                                                                                                                                                                                                                                        e (%) 
              Module I                                                                                                                                                                                                                        20 
              Descriptors/Topics: Introduction and basic programming with Python 
              History, Features, Working with Python, Basic Syntax, Variable and Data Types, Operator, Expression and Statements. Understanding the 
              programming  constructs with   If , If- else, Nested if-else, For loop ,While loop ,Nested loops, Break ,Continue ,Pass 
              Module II                                                                                                                                                                                                                       30 
               Descriptors/Topics: Python  advanced programming 
               Function and methods, Recursion, Exception handling. List: Traversing, List operation, list slices, list method, list and strings, Tuples: tuple 
               assignment, tuple as a return type, list and tuples, Dictionary: Dictionary as a set of counter, Looping and dictionaries .Creating a GUI that 
               handles an event using tkinter package. Controlling layout with geometry manager pack(), place() and grid() methods , graphically visualizing 
               the data using matplotlib package .  Introduction of numpy package with  different functions  
              Module III                                                                                                                                                                                                                      30 
              Descriptors/Topics: Basics commands in Bio-Python                                                                                                                                                                               
              Storing strings in variables, DNA concatenation, finding length of a string, extracting sub-strings, reading text from a file, writing text to a 
              file, reading and writing a FASTA file, Splitting a string to make a list, Percentage of amino acid residues. 
              Module IV                                                                                                                                                                                                                       20 
              Descriptors/Topics: Bioinformatics analysis using Python 
              Searching for a pattern in a string, Building Seq sequences from strings, Plotting codon frequency, Fetching a SwissProt entry from a file, 
              SwissProt to FASTA, Running Blast and Clustalw. 
        
            Pedagogy for Course Delivery: 
                        Lectures:32 
                        Tutorials: 0 
                        Presentation/ Seminar/Quiz: 1 
                        Class Test: 2 
                        Total: 35 
                         
            Practical                    
            Practical                :    28 
            Lab internal             :   2 
            Total                    :   30 
       PSDA activity: Group discussion, Guest lecture  
       List of Experiments: 
     
           1.  Create and run Python programs using basic scalars. 
           2.  Implement and manipulate strings, functions, operators, lists, loops, and arrays. 
           3.  Format output and list content. 
           4.  Read external files in Python. 
           5.  Create practical programs that interact with the user and the operating system. 
           6.  Designing a GUI of Hospital Management system using Tkinter Package. 
           7.  Design different types of Charts using matplotlib package :   
           8.  Design a program to find out the percentage of amino acid residues in a PDB file. 
           9.  BIO PYTHON 
               
       Assessment/ Examination Scheme: 
                            Theory L/T (%)                           Lab/Practical/Studio (%)                                  Total 
                              75%                                              25%                                             100% 
                                       Continuous Assessment/Internal Assessment (50%)                                                  End Term 
                                                                                                                                       Examination (50%) 
        Components            Class Test 1              Class Test 2                  Home            QUIZ/MCQ         Attend      
        (Drop down)                                                                Assignment                           ance 
       Weightage (%)              15                        15                         10                                5                     
                                                                                                            5                                50 
                                                                                                             
       Theory Assessment (L&T): 
       Lab/ Practical/ Studio Assessment: 
                              Continuous Assessment/Internal Assessment (50%)                                          End Term Examination 
                                                                                                                               ( 50%) 
        Components         Lab Test       Lab Record         Home             VIVA          Attendance       Lab Test       Lab Record          Viva 
       (Drop down)                                        Assignment 
      Weightage (%)           15              10               10                               5               10               25              15 
                                                                               10 
                                                                                  
        
                                            Mapping Continuous Evaluation components/PSDA with CLOs 
      
                                         Bloom’s Level   Remembering  Understanding  Applying       Analyzing  Evaluating  Creating 
                                              > 
                                              Course     CLO1            CLO2               CLO3  CLO4             CLO5  CLO 6 
                                              Learning    
                                              Outcomes  
                                          
                                          
                                         Assessment 
                                         type/PSDA 
                                         Class Quiz                                                                              
                                         Home                                                                             
                                         assignment 
                                         Presentation                                                   √           √               
                                         /Seminar 
                                         Class Test 1                                                                     
                                         Class Test 2          √                                                                   
                                         Viva                                                   √                  √               
                                         Lab record                                                                     
                                         Lab                                                                             √ 
                                         Performance 
         
        Text Books / Online   : 
      
            •  Jason Kinser, “Python for Bioinformatics”, Jones & Bartlett Publishers, 2008. 
            •  Mark Lutz, “Learning Python”, 3rd edition, O'Reilly, 2007. 
            •  Alex Martelli, David Ascher, “Python cookbook”, O'Reilly, 2002. 
            •  Libeskind-Hadas, Ran, and Eliot Bush. Computing for biologists: Python programming and principles. Cambridge University Press, 2014. 
            •  www.javatpoint.com ,  
      
               REFERENCE 
      
            •  http://www.biopython.org 
            •  Marin-Sanguino, Alberto. "Book Review: Computing for Biologists: Python Programming and Principles." Frontiers in Genetics 7 (2016): 86.