People

Sayoni Das

Job: PhD Student
Website: http://sayonidas.blogspot.co.uk/
Email: sayoni.das.12@ucl.ac.uk

B.S. Degree: Biotechnology, West Bengal University of Technology, 2010.

M.S. Degree: Biochemical Engg. & Biotechnology, IIT Delhi, 2012.

PhD Degree: Bioinformatics, University College London, 2016.

Bio: My PhD project aims to develop new methods for predicting the functions of uncharacterised proteins and identifying conserved residues associated with protein functional sites. Due to the rapid increase in genome-sequencing and structural genomics initiatives, a large amount of sequence data (and in some cases, structural data) is now available. Since experimental characterisation of such huge amounts of data is not feasible, computational function prediction methods are required to predict the functions of proteins. I am using the in-house protein family resource to functionally classifying proteins and recognise sites important for function. This site data will be particularly valuable in a clinical context where residue mutations (nsSNPs) are being analysed to build diagnostic tests for particular diseases or treatment regimes. The methods will be tested in collaboration with groups undertaking research into gut bacterial proteins important for heath in humans and also proteins linked to heart disease. I am also interested in identifying uncharacterised families which appear to have very different conserved residues and likely novel chemistries.


Sayoni Das

Job: PhD Student
Website: http://sayonidas.blogspot.co.uk/
Email: sayoni.das.12@ucl.ac.uk

B.S. Degree: Biotechnology, West Bengal University of Technology, 2010.

M.S. Degree: Biochemical Engg. & Biotechnology, IIT Delhi, 2012.

PhD Degree: Bioinformatics, University College London, 2016.

Bio: My PhD project aims to develop new methods for predicting the functions of uncharacterised proteins and identifying conserved residues associated with protein functional sites. Due to the rapid increase in genome-sequencing and structural genomics initiatives, a large amount of sequence data (and in some cases, structural data) is now available. Since experimental characterisation of such huge amounts of data is not feasible, computational function prediction methods are required to predict the functions of proteins. I am using the in-house protein family resource to functionally classifying proteins and recognise sites important for function. This site data will be particularly valuable in a clinical context where residue mutations (nsSNPs) are being analysed to build diagnostic tests for particular diseases or treatment regimes. The methods will be tested in collaboration with groups undertaking research into gut bacterial proteins important for heath in humans and also proteins linked to heart disease. I am also interested in identifying uncharacterised families which appear to have very different conserved residues and likely novel chemistries.


Sayoni Das

Job: PhD Student
Website: http://sayonidas.blogspot.co.uk/
Email: sayoni.das.12@ucl.ac.uk

B.S. Degree: Biotechnology, West Bengal University of Technology, 2010.

M.S. Degree: Biochemical Engg. & Biotechnology, IIT Delhi, 2012.

PhD Degree: Bioinformatics, University College London, 2016.

Bio: My PhD project aims to develop new methods for predicting the functions of uncharacterised proteins and identifying conserved residues associated with protein functional sites. Due to the rapid increase in genome-sequencing and structural genomics initiatives, a large amount of sequence data (and in some cases, structural data) is now available. Since experimental characterisation of such huge amounts of data is not feasible, computational function prediction methods are required to predict the functions of proteins. I am using the in-house protein family resource to functionally classifying proteins and recognise sites important for function. This site data will be particularly valuable in a clinical context where residue mutations (nsSNPs) are being analysed to build diagnostic tests for particular diseases or treatment regimes. The methods will be tested in collaboration with groups undertaking research into gut bacterial proteins important for heath in humans and also proteins linked to heart disease. I am also interested in identifying uncharacterised families which appear to have very different conserved residues and likely novel chemistries.


Sayoni Das

Job: PhD Student
Website: http://sayonidas.blogspot.co.uk/
Email: sayoni.das.12@ucl.ac.uk

B.S. Degree: Biotechnology, West Bengal University of Technology, 2010.

M.S. Degree: Biochemical Engg. & Biotechnology, IIT Delhi, 2012.

PhD Degree: Bioinformatics, University College London, 2016.

Bio: My PhD project aims to develop new methods for predicting the functions of uncharacterised proteins and identifying conserved residues associated with protein functional sites. Due to the rapid increase in genome-sequencing and structural genomics initiatives, a large amount of sequence data (and in some cases, structural data) is now available. Since experimental characterisation of such huge amounts of data is not feasible, computational function prediction methods are required to predict the functions of proteins. I am using the in-house protein family resource to functionally classifying proteins and recognise sites important for function. This site data will be particularly valuable in a clinical context where residue mutations (nsSNPs) are being analysed to build diagnostic tests for particular diseases or treatment regimes. The methods will be tested in collaboration with groups undertaking research into gut bacterial proteins important for heath in humans and also proteins linked to heart disease. I am also interested in identifying uncharacterised families which appear to have very different conserved residues and likely novel chemistries.