Karthik Raman

Associate Professor
Co-ordinator, Initiative for Biological Systems Engineering
BT 221, Block II, Department of Biotechnology
Bhupat & Jyoti Mehta School of Biosciences
Indian Institute of Technology Madras
Chennai – 600 036

Curriculum Vitaé PDF


We are an interdisciplinary group focussing on the development of algorithms and computational tools to understand, predict and manipulate complex biological networks.

Work in our lab broadly falls under four related themes:

  1. Understanding microbial interactions in microbiomes
  2. In silico metabolic engineering
  3. Theoretical investigations of biological networks
  4. Biological data analysis

We are also an active member of the Initiative for Biological Systems Engineering, and the Robert Bosch Centre for Data Sciences and Artificial Intelligence (RBC-DSAI) at IIT Madras.

(1) Understanding microbial interactions in microbiomes

Building on our expertise in metabolic modelling, we have now initiated studies of several microbiomes and microbial interactions in these microbiomes. Building on our MetQuest algorithm and Metabolic Support Index to understand microbial metabolic

interactions, we are now studying microbiomes as diverse as the Guaymas Basic hydrothermal vents to the International Space Station microbiome. We are also very much interested in studying the gut microbiome and the role of keystone species in any microbiome.


  • Studying microbial interactions in the ISS microbiome
  • Variations in the ocular microbiome between healthy and keratitis conditions
  • Gut microbiome: interactions and organisation

Relevant Publications

(2) In silico Metabolic Engineering

We develop computational approaches to predict ways to manipulate metabolic networks, for the over-production of commercially important molecules, e.g. hyaluronic acid, α-tocopherol. We primarily focus on constraint-based approaches to study metabolic networks, using tools such as flux balance analysis. We also have collaborations with experimental labs, to validate the predicted metabolic engineering strategies.


  • Rational design of a consortium for metabolic engineering
  • Overproduction of α-tocopherol in H. annuus cell lines
  • Overproduction of hyaluronic acid in L. lactis
  • Predicting novel metabolic pathways for retrosynthesis

Relevant Publications

(3) Theoretical Investigations of Biological Networks

A lot of our work involves a fundamental understanding of biological networks, such as metabolic networks. We try to answer fundamental questions about the organisation and evolution of these networks, in a bid to better understand the constraints that permeate their design. This, in turn, will be very helpful towards designing and manipulating such networks, for various applications, including metabolic engineering.


  • Understanding synthetic lethality in metabolic networks
  • Robustness and plasticity of metabolic networks
  • Design principles of oscillators, network design for synthetic biology
  • Systems-theoretic approaches to design adaptive networks
  • Sloppiness in biological systems

Relevant Publications

(4) Biological Data Analysis

We are also working on a data-centric investigation of biological networks. For example, how can we understand biological networks, by using multi-dimensional data (e.g. genomic, transcriptomic, proteomic, phosphoproteomic etc.)? We also apply techniques from machine learning to study biological networks and datasets  alike, to make testable predictions and generate hypotheses for wet lab experimentation.


  • Predicting essential proteins in protein interaction networks (See NetGenes database)
  • Identifying disease modules in biological networks [DREAM Challenge]
  • Identifying the context of mutations in cancer (DBT Project)

Relevant Publications




  • BT5240 Computational Systems Biology (Jan-May)
  • BT2020 Numerical Methods for Biology (Jan-May), along with Dr. Athi N. Naganathan
  • BT3051 Data Structures and Algorithms for Biology (Jul-Nov)
  • BT4310 Current Topics in Synthetic Biology (Jul-Nov)



  • BT5240 Computational Systems Biology (Jan-May)
  • AICTE STTP on Computational Systems Biology (Feb 6-11)
  • BT3051 Data Structures and Algorithms for Biology (Jul-Nov)
  • BT4110 Computational Biology Laboratory (Jul-Nov)
  • BT1010 Life Sciences – Module on “Big Data in Biology”


  • BT5240 Computational Systems Biology (Jan-May)
  • BT3051 Data Structures and Algorithms for Biology (Jul-Nov)
  • BT4110 Computational Biology Laboratory (Jul-Nov)


  • BT5240 Computational Systems Biology (Jan-May)
  • BT3051 Data Structures and Algorithms for Biology (Jul-Nov)
  • BT4110 Computational Biology Laboratory (Jul-Nov)


  • BT5240 Computational Systems Biology (Jan-May)
  • BT3051 Data Structures and Algorithms for Biology (Jul-Nov)
  • BT4310 Current Topics in Synthetic Biology (Jul-Nov)


  • BT5240 Computational Systems Biology (Jan-May)
  • BT3240 Metabolic Regulation (Jul-Nov)


  • BT3190 Metabolic Regulation (Jul-Nov)


  • BT3190 Metabolic Regulation (Jul-Nov)

Other Stuff

Read about my other interests and some personal stuff
A collection of interesting quotes, related to biology/systems biology/modelling
Links I use regularly
Friends, colleagues, random interesting people
What I Use
Some of the tools I use to get my work done


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