Manav has been initiated to create a unified database of molecular network of all the tissues in the human body and to derive a holistic picture of working of human body. The project named Manav has been launched by the Department of Biotechnology and Persistent Systems, a biotechnology company.
This mega project will collate and integrate molecular information on human tissues and organs that currently lies hidden in research articles in an unstructured and disorganized form. The project would utilize large biological community, both students and scientists, for extracting and adding the information from scientific literature at the level of cells and organs. The database would eventually help researchers in identifying gaps in current knowledge and help in future projects in diagnostics and disease biology.
The idea emerged from the success of “Smart India hackathon”, a nationwide contest in which large number of engineering students are being encouraged to find solutions to the pressing problems. In the same way, Manav will engage biology students to build their skills in reading scientific literature and deepen their understanding of biological system.
In this public-private venture, DBT and Persistent Systems will invest Rs 13 crore and Rs 7 crore respectively. The project will be executed by Indian Institute of Science Education and Research (IISER) and National Center for Cell Sciences (NCCS) based at Pune. While the institutes will train students, the technology platform and data management will be provided by the private partner. Students and faculty from DBT Star colleges and Biotechnology Information network system (BTIS) network will also be involved.
The project team is in talks with other scientific agencies such as the All India Council of Technical Education, Council of Scientific and Industrial Research (CSIR), University Grants Commission and Indian Council of Medical Research (ICMR) for possible collaboration.
The project will be executed in four steps. First will be creation of a robust online data annotation platform. Second step would involve data annotation and curation by students on the platform. Evaluation of generated data and model by faculty and then senior scientists for quality check would constitute third step. Finally, integration of data, model building and visualization.