Teaching and research Programmes in Computational and Systems Biology involve the research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. In addition, research Programmes involve the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems. The School has initiated a Programme in Complex Systems which will study the behavior of mathematical, physical, living and social systems, identify patterns that underlie these inter-related systems, and examine properties such as emergence, evolution, network, structure and dynamics of these systems in a competitive environment.
The School has encouraged intake from multiple disciplines into all these Programmes - Information Technology, Engineering Sciences, Bioinformatics, the Life Sciences/Biotechnology, the Physical and Chemical Sciences, among others.
Teaching and research Programmes are ably supported by good computational and communication infrastructure. Each student is provided with a personal workstation, and the School manages a centralised facility for high-performance computers, consisting of computer clusters with multiprocessor nodes, large-memory nodes and GPUs to facilitate specialized research.
M.Sc. degree in Computational and Integrative Sciences
The School runs an MSc program in Computational and Integrative Sciences, funded by the Department of Biotechnology at present with a specialization in either Computational Biology or Complex Systems. The program aims to provide a rigorous training, equipping the students with theoretical understanding and practical mastery in the state-of-art computational and experimental techniques to model and analyze the biological and complex systems. In the first year of the program, the students are provided with the conceptual knowledge in the biological sciences, computer programming, physical sciences, mathematics, and statistics including data analytical skills required in the new phase of analysis and understanding of large-scale data. In the second year, the students are familiarized with advanced skill sets, including methods in omics, big data analytics, mathematical modelling and computer simulation etc. followed by specialized research projects that apply the core skills taught in the previous semesters.
The curriculum leading to the award of M. Sc. degree is spread over a period of four semesters – one Monsoon Semester and one Winter Semester in each year. In addition, a project/dissertation work will be executed and a report to be submitted by the student at the end of the 2nd year.
Sub. Code & Sub. Code Number | Eligibility |
Computation and Integrative Sciences - CISM (232) | Admissions will be through the GRADUATE APTITUDE TEST - BIOTECHNOLOGY (GATB) examination conducted by the DBT. (For details on admission, prospective candidates may visit the Regional Centre for Biotechnology (RCB), Faridabad/DBT/JNU website) |
Course Structure : Download
P.G. Diploma in Big Data Analytics
Post-Graduate Diploma in Big Data Analytics (PGD), with specialization in Biological Big Data. This skill development program is aimed at training postgraduates in the upcoming field of Big Data analytics in life sciences and health. The trained graduates from this program are expected to learn key technologies of data sciences, such as machine learning, data integration and modeling technologies, which can be applied in an academic, and industry environment in the future.
The curricular work leading to the award of Post- Graduate Diploma is spread over a period of two semesters – one Monsoon Semester and one Winter Semester with a provision of a project report to be submitted by student at the end of the Winter Semester. The admissions to PGD program is through Entrance Examination.
ADMISSION TO PROGRAMMES OF STUDY- For admissions, to PGD programs is through Entrance Examination.
Name of School |
Sub. Code & Sub. Code Number |
Eligibility |
NTA Test paper code |
School of Computation al and Integrative Sciences (SC&IS) |
Post-Graduate Diploma in Big Data Analytics - PGDT (191) |
M.Sc/B.Tech/B.E. in Physics/ Chemistry/ Mathematics/Computer Science/ Statistics/ Operations research/ Life Sciences/ Biotechnology/ Bioinformatics/ related disciplines in engineering, physical, and biological sciences. Minimum of 55% in the qualifying degree. |
PGQP26 |
Course Structure - Download
The School runs a vibrant Ph.D. program, with research in different areas of Computational Biology and Complex Systems.
Some of the frontier areas of research conducted at the School are:
- - Computational Genomics and Next Generation Sequencing.
- - Applied data analytics and machine learning.
- - Plant Biology: Genomics, Epigenomics and Genome Editing Single Cell Genomics,
- - Multi-omics and Systems Biology.
- - Cheminformatics and Drug Discovery.
- - Genome-wide Application of Information Theory and Pattern Recognition Methods.
- - DNA-Protein Interactions.
- - Nucleosome Dynamics.
- - Genome Organisation and Function Biomechanics.
- - Mathematical Modeling of the biological systems.
- - Stochastic and Nonlinear Dynamics Applied to Biological Systems.
- - Monte Carlo Simulation Techniques to Explore the Energy Landscape of Water Clusters and Biomolecules Structure.
- - Function, dynamics of calcium-binding proteins.
- - Development of a Bacterial Cell Model: diffusion and hydrodynamics.
- - Effect of Molecular Crowding on Biomolecular Systems.
- - Mathematical biology.
- - Graph Theory and Petri-Nets optimization techniques.
- - Application of Network Theory in Social and Financial Systems.
- - Econophysics and Sociophysics- Application of Physics to Model Socio-Economic Systems.
- - Wireless communication and Applications in Biology, including wearable/implantable devices as antennas/sensors.
- - High Performance Computing and Cyber infrastructure.
- - Biomolecular Interactions, nano- and bio-sensor for clinical, food and environment applications.
Admission:
The admission to PhD program is through JNU Entrance Examination. Entrance examination will consist of a choice from two or three tracks for Ph.D. programme based on the academic background of applicants. In addition, students who have cleared the National Eligibility Test & hold a Junior Research Fellowship (JRF) may be invited directly for the viva/interview for admission to Ph.D. Courses. The prospective candidates are requested to visit the JNU admissions related webpage/s regularly to know the latest updates/eligibility criteria erc. on admissions and related information.
Admission in the Ph.D. programme at SCIS would be under three tracks:-
Track 1: Physical Sciences: Physics, Chemistry and related disciplines.
Track 2: Biological Sciences: Life Sciences, Biotechnology and related disciplines with an aptitude in informatics; Bioinformatics and Computational Biology.
Track 3: Mathematical and Computer Sciences: Mathematics/Statistics, Computer Sciences including Information Technology with emphasis on data analytics.
The use of the word “Track” in this document is solely for the purpose of grouping disciplines for the purpose of Entrance examination and admission to various programs.
Note: Candidates applying for Ph.D. programme are allowed to exercise only one track for each programme.
Selection of students to these programmes is through the JNU entrance examination/interview. Please see the official JNU web site http://jnu.ac.in for more information on eligibility, exam schedule , fees, etc.