About the Project

Homa Mohammadi Peyhani

Project 5:  A database with hypothetical reactions, and their associated putative sequences, between 70K known biological molecules.

BridgIT: A database of reaction similarities rules for the compasrison of reactions based on the structural similarity of their substrates and products. Basicly, BridgIT introduces, for the first time, information about the enzyme binding pocket into reaction similarity comparisons. BridgIT assesses the similarity of two reactions, one orphan and one non-orphan, using the reactive sites of their substrates and their neighborhood structures, along with the structures of the generated products, and then suggests protein sequences and genes of the most similar non-orphan reactions as candidates for catalyzing the orphan ones.
Application: Assigning sequences of known reactions to orphan and novel reactions, which lack gene associations. The candidate enzymes for the de novo/orphan  reactions are either immediately capable of catalyzing these reactions or can serve as initial sequences for enzyme engineering. The obtained BridgIT similarity scores can also be used as a confidence score to assess the feasibility of the implementation of novel ATLAS reactions in metabolic engineering and systems biology studies.

BNICE: Application of the reaction and pathway prediction framework (BNICE) for the construction of databases of novel reactions between compounds in chemical databases and compounds in biological databases."

More information: http://lcsb.epfl.ch/ 

Research Interests


I am currently a  PhD student in the Laboratory of Computational Systems Biotechnology at EPFL under supervision of Prof. Vassily Hatzimanikatis. 
Prior to my enrolment at EPFL I got my MSc. and BSc. in Chemical Engineering at Sharif University of Technology in Iran. My major was Process Control and I did my master's thesis  under the supervision of Prof. Bozorgmehry. During my  master project, I focused on application of artificial intelligence and programming in Metabolic Networks identification. I employed Ontology Theory to develop a multi-agent framework for synthesising, characterisation and behaviour analysis (statical  and dynamical) of metabolic networks. My primary research interests are computational biology and metabolic engineering to bring about new methods for biotechnological applications. I am also interested in developing algorithms for processing massive data sets, and digital and adaptive control in novel systems.