We are Sharma Lab, and our laboratory is interested in developing and applying network medicine approaches to human disease. You can discover more about network medicine and our objectives here!
We are interested in the application of systems biology and network science methods to understand the cause of human disease, and the application of systems pharmacology approaches to develop new disease treatments and preventative strategies...
My lab is interested in elucidating the fundamental cellular and molecular processes that underlie memory formation. In particular we are interested in the elucidation of the protein machinery at the synapse that governs long-term storage of information, and how basic cell biological processes have been elaborated in neurons for the purpose of modulating synaptic transmission...
Sharmalab at Channing division of Network medicine focuses on broad area of systems medicine and high throughput experimental data ranging from genomics to health care records. We explore the relationship between different type of interaction networks...
Network medicine deals with complexity by “simplifying” complex systems, summarizing them merely as components (nodes) and interactions (edges) between them. As regards cellular systems, the nodes can be metabolites and macromolecules such as proteins, RNA molecules and gene sequences, while the edges are physical, biochemical and functional interactions that can be identified with a plethora of technologies. One of the main predictions is that the human disorders should be viewed as perturbations of different types of networks. The quantification and mathematical modeling of nodes and edges provides us the information about disease and healthy states.
Sharmalab at Channing division of Network medicine focuses on broad area of systems medicine and high throughput experimental data ranging from genomics to health care records. We explore the relationship between different type of interaction networks and human disease and aim to gain a deeper knowledge of the molecular bases of pathological processes. The complexity of biological systems motivates us to use network and computational based to provide deep understanding of disease etiology. A deeper knowledge of the cell networks and molecular bases that drive pathological processes will inspire novel therapeutic strategies, ultimately leading to the development of more effective and safer drugs to fight complex diseases. We focus on providing the prominent predictive models to integrate 'omics' data aided by the systems and network biology. An integrated understanding of the interactions among the genome, the proteome, the environment and the pathophenome, mediated by the underlying cellular network, offers a basis for future advances. Such advances will help us to understand the structure and the workings of the wiring diagram — the prerequisite towards identifying the components whose functions need to be maintained and those whose activity must be altered with drugs.
Channing Division of Network Medicine
Center of Complex Network Research, Northeastern University
Center for Cancer Systems Biology, Dana Farber Cancer Institute
Sharma Lab - Channing Division of Network Medicine
Harvard Medical School
181 Longwood Avenue, Office: 512
Boston, MA 02115
US Patent Application Status: Filed June 2013 - Not Yet Received
We describe an algorithm that identifies genes and gene products of putative relevance to any given disease. The algorithm uses the topology of cellular protein-protein networks and a given set of known diseases associated protein to produce a raking to all other proteins according to their potential relevance to the die disease. Ultimately, a so-called disease-module is identified, i.e. the local neighborhood within the protein interaction network that is responsible for the particular disease phenotype. The disease module can (i) provide insights into the function of important genes, (ii) elucidate important pathways and (iii) facilitate the identification of potential drug targets.
My broad interests are in the application of network science for medicine and collaborative projects. My areas of focus are personalized medicine, miRNA impact on disease modules, dynamics of biological networks, and team success in research.
Visualization Design Advisor