Intro Genome Bio 2013: Difference between revisions

From QiuLab
Jump to navigation Jump to search
imported>Weigang
imported>Weigang
Line 8: Line 8:
==General Information==
==General Information==
===Course Description===
===Course Description===
* '''Background:''' Biomedical research is becoming a high-throughput science. As a result, information technology plays an increasingly important role in biomedical discovery. Bioinformatics is a new interdisciplinary field formed between molecular biology and computer science.
* '''Background:''' A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and rapid DNA-sequencing technologies, biomedical sciences are undergoing a rapid and profound transformation into a highly data-intensive field, which requires familiarity with concepts in both biology and computer science. Genome information is revolutionizing virtually all aspects of biology and medicine and will lead to major advances such as more efficient production of renewable energy, better cures for cancers, and longer and healthier life expectancy.  
* '''Contents:''' This course will introduce both bioinformatics '''theories''' and '''practices'''. Topics include: database searching, sequence alignment, molecular phylogenetics, structure prediction, and microarray analysis. The course is held in a UNIX-based instructional lab specifically configured for bioinformatics applications.
* '''Contents:''' This course will introduce genome-sequencing technologies, explore genome projects online, and discuss both the benefits and challenges (e.g., ethical and legal) of the genomic revolution to society.
* '''Problem-based Learning (PBL):'''  For each session, students will work in groups to solve a set of bioinformatics problems. Instructor will serve as the facilitator rather than a lecturer. Evaluation of student performance include both active participation in the classroom work as well as quality of assignments (see [[#Grading Policy]]).
* '''Learning Goals:''' After competing the course, students should be able to perform most common bioinformatics analysis in a biomedical research setting. Specifically, students will be able to
* '''Learning Goals:''' After competing the course, students should be able to perform most common bioinformatics analysis in a biomedical research setting. Specifically, students will be able to
** Approach biological questions evolutionarily ("Tree-thinking")
**  
** Evaluate and interpret computational results statistically ("Statistical-thinking")
** Evaluate and interpret computational results statistically ("Statistical-thinking")
** Formulate informatics questions quantitatively and precisely ("Abstraction")
** Formulate informatics questions quantitatively and precisely ("Abstraction")
** Design efficient procedures to solve problems ("Algorithm-thinking")
** Design efficient procedures to solve problems ("Algorithm-thinking")
** Manipulate high-volume textual data using UNIX tools, Perl/BioPerl, R, and Relational Database ("Data Visualization")
** Manipulate high-volume textual data using UNIX tools, Perl/BioPerl, R, and Relational Database ("Data Visualization")
* '''Pre-requisites:''' This 3-credit course is designed for upper-level undergraduates and graduate students. Prior experiences in the UNIX Operating System and at least one programming language are required. Hunter pre-requisites are CSCI132 (Practical Unix and Perl Programming) and BIOL300 (Biochemistry) or BIOL302 (Molecular Genetics), or permission by the instructor. '''Warning: This is a programming-based bioinformatics course. Working knowledge of UNIX and Perl is required for successful completion of the course.'''
* '''Textbook:''' Arthur Lesk (2012). ''Introduction to Genomics'' (2nd Edition). Oxford University Press. [http://www.amazon.com/Introduction-Genomics-Arthur-M-Lesk/dp/0199564353/ref=sr_1_1?ie=UTF8&qid=1378143035&sr=8-1&keywords=introduction+to+genomics Amazon Link]
* '''Textbook:''' Krane & Raymer (2003). ''Fundamental Concepts of Bioinformatics''. Pearson Education, Inc. (ISBN 0-8053-4633-3)
* '''Academic Honesty:''' Hunter College regards acts of academic dishonesty (e.g., plagiarism, cheating on examinations, obtaining unfair advantage, and falsification of records and official documents) as serious offenses against the values of intellectual honesty. The College is committed to enforcing the CUNY Policy on Academic Integrity and will pursue cases of academic dishonesty according to the Hunter College Academic Integrity Procedures.
* '''Academic Honesty:''' Hunter College regards acts of academic dishonesty (e.g., plagiarism, cheating on examinations, obtaining unfair advantage, and falsification of records and official documents) as serious offenses against the values of intellectual honesty. The College is committed to enforcing the CUNY Policy on Academic Integrity and will pursue cases of academic dishonesty according to the Hunter College Academic Integrity Procedures.



Revision as of 17:33, 2 September 2013

BIOL 105. Introduction to Genome Biology (Fall 2013)
Instructor: Dr Weigang Qiu, Associate Professor of Biology
Room: C104 Hunter North (a Computer Lab)
Hours: Tuesdays, 12:45-3:15PM
Office Hours: Room 839 HN; Wednesdays 5-7pm or by appointment
Phone: 212-772-5296

General Information

Course Description

  • Background: A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and rapid DNA-sequencing technologies, biomedical sciences are undergoing a rapid and profound transformation into a highly data-intensive field, which requires familiarity with concepts in both biology and computer science. Genome information is revolutionizing virtually all aspects of biology and medicine and will lead to major advances such as more efficient production of renewable energy, better cures for cancers, and longer and healthier life expectancy.
  • Contents: This course will introduce genome-sequencing technologies, explore genome projects online, and discuss both the benefits and challenges (e.g., ethical and legal) of the genomic revolution to society.
  • Learning Goals: After competing the course, students should be able to perform most common bioinformatics analysis in a biomedical research setting. Specifically, students will be able to
    • Evaluate and interpret computational results statistically ("Statistical-thinking")
    • Formulate informatics questions quantitatively and precisely ("Abstraction")
    • Design efficient procedures to solve problems ("Algorithm-thinking")
    • Manipulate high-volume textual data using UNIX tools, Perl/BioPerl, R, and Relational Database ("Data Visualization")
  • Textbook: Arthur Lesk (2012). Introduction to Genomics (2nd Edition). Oxford University Press. Amazon Link
  • Academic Honesty: Hunter College regards acts of academic dishonesty (e.g., plagiarism, cheating on examinations, obtaining unfair advantage, and falsification of records and official documents) as serious offenses against the values of intellectual honesty. The College is committed to enforcing the CUNY Policy on Academic Integrity and will pursue cases of academic dishonesty according to the Hunter College Academic Integrity Procedures.

Grading Policy

  • Treat assignments as take-home exams. Student performance will be evaluated by weekly assignments and projects. While these are take-home projects and students are allowed to work in groups and answers to some of the questions are provided in the back of the textbook, students are expected to compose the final short answers, computer commands, and code independently. There are virtually an unlimited number of ways to solve a computational problem, as are ways and personal styles to implement an algorithm. Writings and blocks of codes that are virtually exact copies between individual students will be investigated as possible cases of plagiarism (e.g., copies from the Internet, text book, or each other). In such a case, the instructor will hold closed-door exams for involved individuals. Zero credits will be given to ALL involved individuals if the instructor considers there is enough evidence for plagiarism. To avoid being investigated for plagiarism, Do NOT copy from others or let others copy your work.
  • Submit assignments in Printed Hard Copies. Email attachments will NOT be accepted. Each assignment will be graded based on timeliness (10%), whether executable or having major errors (50%), algorithm efficiency (10%), and readability in programming styles (30%, see #Assignment Expectations).
  • The grading scheme
    • Assignments (100 pts): 10 exercises.
    • Mid-term (50 pts).
    • Final Project (50 pts)
    • Classroom performance (50 pts): Active engagement in classroom exercises and discussions
    • Attendance (50 pts): 1 unexcused absences = 40; 2 absences = 30; More than 2 = 0.

Assignment Expectations

  • Use a programming editor (e.g., vi or emacs) so you could have features like automatic syntax highlighting, indentation, and matching of quotes and parenthesis.
  • All PERL code must begin with "use strict; and use warnings;" statements. For each assignment, unless otherwise stated, I would like the full text of the source code. Since you cannot print using the text editor in the lab (even if you are connected from home), you must copy and paste the code into a word processor or a local text editor. If you are using a word processor, change the font to a fixed-width/monospace font. On Windows, this is usually Courier.
  • Also, unless otherwise stated, both the input and the output of the program must be submitted as well. This should also be in fixed-width font, and you should label it in such a way so that I know it is the program's input/output. This is so that I know that you've run the program, what data you have used, and what the program produced. If you are working from the lab, one option is to email the code to yourself, change the font, and then print it somewhere else as there is no printer in the lab.
  • Recommended Style
  • Bad Style

Weekly Schedule (All Tuesdays)

September 10

September 17

September 24

October 1

October 8

October 15. No Class (Monday Schedule)

October 22. Mid-Term Exam

October 29

November 5

November 12

November 19

November 26

December 10

December 17. Final Exam

Links