Computational Systems Biology Lab

Karthik Raman's Lab @ IIT Madras
  • Home
  • Research
    • Publications
    • Collaborators
    • Software & Datasets
  • Teaching
  • People
  • Karthik Raman
    • Bio
    • Talks
    • Links
    • Personal
  • Blog
  • Announcements
  • Press
  • FAQ
  • Contact
  • Home
  • Blogs

Blogs

Category

  • Research articles
  • Books
  • More Categories
    Read Less

Filter by Tag

Filter by Tag

blog-image
Finding the microbial heroes

by Karthik Raman, Aswathy K. Raghu & Indumathi Palanikumar

The algorithm helps in identifying the smallest groups of microbes, capable of executing a desired function, from a large microbial community

Given a large co-operative microbial community, an algorithm to identify the smallest subsets of that community capable of a desired functionality is presented. These subsets, called minimal microbiomes, will contain the keystone species that achieve the required purpose.

Read the full blog article at https://communities.springernature.com/posts/finding-the-microbial-heroes-identifying-the-smallest-groups-of-microbes-capable-of-executing-a-desired-function-from-a-large-microbial-community

• Jul 10, 2024
Know More
blog-image
Research Highlight: Hunting for mini gut microbe clusters

by Nature India

The algorithm — minMicrobiome — could help design personalised treatment strategies for gut microbiome-related diseases, for example by reintroducing lost gut flora in some cases of severe inflammatory bowel disease and Clostridium difficile infections. It could also optimize industrial processes such as chemical production and wastewater treatment, say scientists at the Robert Bosch Centre for Data Science and Artificial Intelligence at Indian Institute of Technology Madras in Chennai.

• Jul 5, 2024
Know More
blog-image
Towards Personalised Cancer Treatment

by Aditi Jain

Although, there does exist tools that identify personalized cancer genes, however, they use unsupervised learning method and predicts based on the presence and absence of mutations in cancer-related genes. This study, however, is the first one to use the supervised learning method by applying gene-based labelling that is cancer-specific. This new model also takes into account the functional impact of the mutations while making predictions.

“ The research area of precision medicine is still at a nascent stage. PIVOT helps push these boundaries and presents prospects for experimental research based on the genes identified,” says Malvika Sudhakar, lead author of the study.

• Jul 21, 2022
Know More
blog-image
A Strategy To Make Networks More Resilient To Attacks

by Aditi Jain

“A variety of technological networks form the backbone of modern world infrastructure, and it is very essential to build safeguards to protect these networks against both failures and targeted attacks,” says Dr Karthik Raman, Associate Professor at the Bhupat & Jyoti Mehta School of Biosciences and a core member of the Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras.

Dr Karthik Raman and his student Mr. Sai Saranga Das worked on this problem and have come up with a strategy that makes the networks more resilient to adverse attacks. The strategy basically suggests a way of judiciously re-wiring a given network to reduce the risk of network failure due to any adverse attack. The research work has been published in an esteemed research journal Physica A: Statistical Mechanics and its Applications.

• Jun 16, 2022
Know More
blog-image
Discovering Cellular Networks for Biological Adaptation

by Akshay Anantharaman

In this study, the authors of this paper —Mr. Priyan Bhattacharya and Prof. Arun K. Tangirala from the Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai, India, and Dr. Karthik Raman from the Department of Biotechnology, Indian Institute of Technology Madras, Chennai, India—have for the first time suggested a generic systems-theoretic approach to unravel the possible networks design configurations for perfect adaptation.  The proposed approach translates the conditions for biological adaptation into precise mathematical equations using systems theory. Further, these equations are mapped back to necessary structural requirements with the help of combinatorial mathematics.

• May 11, 2022
Know More
blog-image
The Hidden Drivers: A Lens into Cancer

by Akshay Anantharaman

A lot of research is happening with regard to cancer, and thankfully, a lot of progress has been made in understanding the aetiology of this complex disease. “Driver” genes are known to play a major role in causing cancer. Many of these genes have been identified, but still many driver genes need to be identified. Till now, only genes that harbour a high rate of mutations, thus causing cancer, have been identified. But what about the numerous driver genes that haven’t been identified?

• Mar 22, 2022
Know More
blog-image
CAMP: The Perfect Bacterial Matchmaker

by Aditi Jain

Dr Karthik Raman, an Associate Professor at IIT Madras and a core member of RBCDSAI, is a scientist whose interest lies in discerning the dynamics of microbial interactions to utilize them for biotechnological application. Recently, Dr Raman and a post-doctoral fellow in his group, Dr Maziya Ibrahim proposed a computational approach named CAMP(Co-culture/Community Analyses for Metabolite Production) which suggests how to bundle two or more bacteria together, forming a community that produces the desired products in maximum quantity. Given the significance of the work, it has been published in a prestigious international _Computational and Structural Biotechnology Journal.

• Mar 8, 2022
Know More
blog-image
Learning systems biology, the computational way

The 90s was an interesting time for biology research as researchers shifted from reductionist to a systems approach for studying and understanding biological systems. A decade later, high-throughput technologies revolutionized the field of systems biology by generating heaps of data. Thanks to these technologies, the state of thousands of genes, proteins, chemicals or metabolites at a given time-point, or in response to any stimuli, can be captured now. However, generating insights from this humongous amount of data was like looking for a needle in a haystack. It was at this time that the need for computation in conducting biology research became apparent and the field of computational biology reached its full glory.

By Karthik Raman
• Feb 25, 2022
Know More
blog-image
The best books on modelling biological systems and networks

Since my undergraduate days studying control theory as a chemical engineer, I’ve been captivated by mathematical models of complex phenomena. These models have a remarkable way of revealing key insights into biological systems, which are often incredibly challenging to understand due to their complexity. With over 15 years of experience as a systems biology researcher, I’ve had the pleasure of reading numerous books that delve into the fascinating intersection of computation and biology, aiming to map the rapidly growing literature in this dynamic field. I hope you find these books engaging and join the authors in exploring the molecular networks that underpin every living cell!

• Feb 21, 2022
Know More
blog-image
Mind The Messenger: Analyzing The SARS-CoV-2 Transcriptome

by Shayantan Banerjee

As we move into the second year of living with the disease, newer scientific discoveries to fight the virus bring hope. We are now optimistic about the development, equitable distribution, and access to safe COVID-19 vaccines to provide acquired immunity against the virus. Around the world, several different types of potential vaccines are in development. If you are still thinking of getting vaccinated, bookmark this article, open a new tab and register for the closest available vaccine slot. The potential benefits of vaccination far outweigh the potential risks. The internet is flooded with news reports of infection among unvaccinated people ( here, here, and here). It is imperative on your part to do your bit to protect yourself and your community.

• Sep 18, 2021
Know More
blog-image
Utilizing the language of DNA to decipher the driving force behind cancer

The overall aim of this experiment is to build a model using machine learning and natural language processing techniques to differentiate between driver and passenger mutations solely based on the raw nucleotide context. It was confirmed that the neighbourhood nucleotide sequences of driver and passenger mutations greatly differed from one another. Using this distinguishing factor, driver mutations could be successfully identified.

Using sophisticated artificial intelligence techniques, the team comprising Mr. Shayantan Banerjee, Prof. Karthik Raman, and Prof. Balaraman Ravindran, developed a novel prediction algorithm called NBDriver.

• Jul 22, 2021
Know More
blog-image
Introducing Students to Systems Biology

The 2013 Nobel citation expresses that “Today the computer is just as important a tool for chemists as the test tube”. That statement is perhaps truer today of biologists, as computation and modelling have taken centre stage in the post-genomic era.

Teaching systems biology

It is easy to convince students about the primacy of a systems approach. But how does one get going? Well, as it turns out, a web browser can be quite handy today, enabling us to tinker with models and ask interesting “what-if” questions. Such questions, which seek to understand the effect of perturbations on networks, form the cornerstone of systems biology.

• Apr 30, 2021
Know More
blog-image

by Aditi Jain

“A classic challenge in biology is to study the function of proteins. Of various functions, essential functions are very interesting, as they map to important indispensable genes in an organism. Experimentally identifying these genes is rather expensive and challenging. Computational predictions can help point in the right direction, to prioritise experiments. To date, experimental data are available for <100 organisms! On the other hand, sequencing data are available for 1000s of organisms, as also interactome (networks of interactions) data. In the paper, we posit that network information is crucial to predict essentiality and achieve excellent performance in prediction, by simply using network data,” explains Dr. Raman.

• Jan 13, 2021
Know More
blog-image
Predicting Essential Genes through Network Approach: Deciphering basis of Life
A classic challenge in biology is to study the function of proteins. Of various functions, essential functions are very interesting, as they map to important indispensable genes in an organism. Experimentally identifying these genes is rather expensive and challenging. Computational predictions can help point in the right direction, to prioritise experiments. To date, experimental data are available for <100 organisms! On the other hand, sequencing data are available for 1000s of organisms, as also interactome (networks of interactions) data.
By V Senthamizhan , By B Ravindran
• Jan 13, 2021
Know More
blog-image
Do you desire good digestion? These small bugs in your gut may help!

by Aditi Jain

Dr. Karthik Raman’s research team from IIT Madras has been working to understand the role played by a specific class of bacteria called Bifidobacteria in the human gut. Recently, they published their research findings in the journal Scientific Reports. Members of Bifidobacteria had earlier shown to be present in the intestine and oral cavity of humans, intestines of insects and in sewage. These bacteria have a number of enzyme-coding genes associated with the metabolism of complex and non-digestible carbohydrates such as milk and plant fibers. They are also known to produce vitamins and antimicrobial substances, regulate the immune system, perform anti-obesity and anti-inflammatory activities which piqued the team’s interest in bacteria.

• Feb 21, 2020
Know More
blog-image
The road not taken: Part II

by Gayathri Sambamoorthy (and Karthik Raman)

One student questioned me, “Is your research about the evolution of microorganisms?” I smiled in happiness that she got something from what I spoke! “Great! Not really! I am coming to that! My research is about understanding how evolution alters reactions in an organism. When the microorganisms evolve, new reactions are added to the pathways. When I mean evolution, it doesn’t just have to be the addition of new reactions. There can also be the removal of reactions from the pathway if the organism thinks it is of no use anymore!”

• Jan 1, 2020
Know More
blog-image
The road not taken: Part I

by Gayathri Sambamoorthy (and Karthik Raman)

Yamini, a class V student, is a very playful child who keenly observes everything around her and comes up with multiple questions that intrigued her. One morning she was angry with her mother that she did not permit her to play in the sand. Seeing the energetic kid unhappy, the teacher took the time to ask her about it.

After Yamini narrated, the teacher decided to explain, " Your mother is right! You may fall sick because of the microbes or microorganisms present." Yamini, confused and curious, said, “I don’t see anything in the sand. How will I fall sick?” The teacher explained, “Microorganisms are small creatures that exist everywhere, and we cannot see them. We can see them only through a microscope!”. She explains and adds further, “There are both harmful and harmless microorganisms.” “What do they eat? They are so tiny!” exclaimed Yamini!

• Jan 1, 2020
Know More
blog-image
Into the microbial world: Navigating through metabolic maps

by Aarthi Ravikrishnan

Ever wondered how food gets digested? How does milk curdle? How do plant litters decompose? Such questions have intrigued me, and I have always wondered what went on behind the screens. Who played a role? Who performed these actions? Was it someone as giant as the Hulk or as tiny as a Lilliputian? Being a biologist, I decided to view them through a magnifying glass (“microscope”) and discovered these complex actions were carried out by tiny little creatures called “micro-organisms”. These micro-organisms are akin to human beings; sometimes they choose to remain single and isolated, while many-a-time tend to stay together as a part of a community. And during their times together, they exhibit the same characteristics as any human being would do: Compete, Cooperate or both.

• Sep 6, 2019
Know More
blog-image
Modelling communities of micro-organisms

Micro-organisms are rarely found to live in isolation in their natural environment. Organisms are found to co-exist in many scenarios, functioning in consolidated and socialising communities. The growing availability of high-throughput sequencing techniques and developments in the field of metagenomics have enabled the generation of large amounts of data about microbial communities. Despite this, sparingly little knowledge is available about the principles governing these ecosystems and interactions among component organisms. The microbial communities have immense unexplored potential – be it in bioprocessing, bioremediation, therapeutics etc. This calls for development of efficient modelling frameworks to shed light on the design principles of these microbial communities.

• Mar 1, 2013
Know More

© 2024 Computational Systems Biology Lab, IIT Madras 2025 | Powered by Megam Solutions' Hugo Theme