Course Name: Introduction to Proteogenomics

Course abstract

Cancer research has been significantly aided by advancements in proteogenomics technologies, where proteomics information derived from mass spectrometry is used to complement genomics using next generation sequencing. With the recent advent of Cancer Moonshot Project, the critical role that proteogenomics can play in improving cancer patient treatment is increasingly being recognized. This workshop will utilize advanced genomic and proteomic technologies and their data from high-quality human biospecimens to identify potentially actionable therapeutic molecular targets. This course is a part of a workshop by experts in the fields of proteomics and proteogenomics in cancer research from the Broad Institute of MIT and Harvard and Indian Institute of Technology Bombay. The course will comprise interactive lectures with case studies, hands-on sessions and demonstrations on proteogenomics aimed at accelerated understanding of cancer. This course will cover the principles of proteogenomics followed by experimental sessions, where proteomics data using LC-MS/MS will be processed and analyzed. The next step will be to integrate the proteomics data with genomics data, from The Cancer Genome Atlas for the proteogenomics analysis. Lectures and demonstrations on different computational methods will be performed for statistical data analysis of proteogenomics data.


Course Instructor

Media Object

Prof. Sanjeeva Srivastava

He is the Group Leader for the Proteomics Laboratory at the Indian Institute of Technology Bombay India -IITB. He obtained his Ph.D. from the University of Alberta and post-doc from the Harvard Medical School in the area of proteomics, stress physiology and has specialized expertise in applications of data enabled sciences in global health, developing country and resource limited settings.

Prof. Srivastava has considerable experience for teaching proteomics courses and conducting hands-on crash-courses on proteomics at IIT Bombay and many other institutes. Apart from the regular research work, Dr. Srivastava has been actively involved in the development of various proteomics e-Learning & Open-Learning curriculums and Virtual Lab initiatives at IIT Bombay generated with an intention to disseminate high-quality educational materials on proteomics at a global scale Ray et al., PLoS Biol. 2012; Ray et al., J Proteomics. 2012; Srivastava et al., Nature 2013.

These Virtual Lab initiatives have been included as a part: Tutorial- IPTP 14 of the International Proteomics Tutorial Programme : supported by Human Proteome Organization - HUPO and European Proteomics Association (EuPA)). Dr. Srivastava teaching efforts has provided him Excellence in Teaching Award in IIT Bombay.

Prof. Srivastava envisions designing novel-framework by linking proteomics and big data for the disruptive innovation by collective intelligence and actionable foresight. He believes strongly in trans-generational capacity building in science, bioengineering and 21st century knowledge society advance the proteomics knowledge for the benefits of global health.


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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jul-Oct 2021

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 Syllabus

 Enrollment : 20-May-2021 to 02-Aug-2021

 Exam registration : 17-Jun-2021 to 17-Sep-2021

 Exam Date : 24-Oct-2021

Enrolled

1194

Registered

59

Certificate Eligible

45

Certified Category Count

Gold

0

Silver

1

Elite

19

Successfully completed

25

Participation

4

Success

Elite

Silver

Gold





Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
    Note:We have taken best assignment score from both July 2020 and July 2021 courses
Introduction to Proteogenomics - Toppers list

AMRUTH DEEPAK BHAT 77%

BASAVESHWAR ENGINEERING COLLEGE (AUTONOMOUS)

ANNWESHA KARGUPTA 73%

MAULANA ABUL KALAM AZAD UNIVERSITY OF TECHNOLOGY, WEST BENGAL

Enrollment Statistics

Total Enrollment: 1194

Registration Statistics

Total Registration : 59

Assignment Statistics




Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.