School of Bioinformatics · Systems & multi-omics
Systems Biology & Network Analysis
Systems biology studies how components interact to produce cellular behaviour. This course teaches network and modelling approaches that turn gene lists into mechanisms you can test.
Course overview
Systems Biology & Network Analysis covers the main kinds of biological network (protein interaction, gene co-expression, regulatory and metabolic), where their data come from, and how much to trust each edge.
You build and analyse networks in Cytoscape and R, find modules and hubs, run enrichment that respects network structure, and write small ordinary-differential-equation models of signalling motifs to see how network shape creates dynamic behaviour.
Learning outcomes
By the end of the course you will be able to:
- Build interaction networks from STRING and curated databases
- Construct co-expression networks and identify modules with WGCNA
- Measure centrality and find network modules
- Run pathway and network-based enrichment
- Write and simulate simple ODE models of signalling motifs
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates of B.Sc., M.Sc., B.Tech., M.Tech., B.Pharm., M.Pharm., MBBS, BDS, B.V.Sc. or a PhD programme in the life sciences, biotechnology, bioinformatics, pharmacy, medicine, agriculture, chemistry, statistics or computer science
- Researchers, faculty and industry professionals moving into data-driven biology
- Final-year students may apply before their results are declared
Prerequisites
- Python or R basics
- Undergraduate molecular biology
Best suited to
- Students with omics results who need to move beyond gene lists
- Biologists interested in mechanism and modelling
- Bioinformaticians adding network methods
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Interaction, regulatory and metabolic networks
- Data sources and confidence
- Graph basics
Topics
- Degree, betweenness and hubs
- Community detection
- Visual encoding in Cytoscape
Topics
- Correlation and soft thresholding
- WGCNA modules and eigengenes
- Linking modules to traits
Topics
- Reactome, GO and WikiPathways
- ORA versus GSEA
- Network propagation
Topics
- Mass-action and Michaelis–Menten kinetics
- Feedback and feed-forward motifs
- Simulation and parameter sensitivity
Topics
- Network construction
- Hypothesis
- Model
Practical sessions and projects
Capstone project
Build a testable hypothesis
Use network analysis and a small dynamic model to turn a list of changed genes into a mechanism with a prediction that an experiment could test.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Networks in biology
Assemble a protein-interaction network around a disease gene set from STRING and filter it by evidence.
- Analysing networks
Identify modules and hubs in the network and design a readable figure.
- Co-expression networks
Build a co-expression network from RNA-seq data and relate modules to sample traits.
- Pathways and enrichment
Compare classic enrichment with network-propagation results for the same gene list.
- Dynamic models
Simulate a negative-feedback loop and a feed-forward loop and explain the dynamics they produce.
- Project: from list to mechanism
Turn an omics gene list into a network-based hypothesis and a small model that makes a testable prediction.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- STRING protein-interaction network: Network construction.string-db.org
- Public RNA-seq series: Co-expression networks.GEO
Core reading
- Shannon P et al. (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Research 13:2498–2504.
- Langfelder P, Horvath S (2008). WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 9:559.
- Alon U. An Introduction to Systems Biology, 2nd edition. CRC Press, 2019.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for Systems Biology & Network Analysis, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for Systems Biology & Network Analysis
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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