000			02638nam a2200301 4500
001			th490
003			ISI Library, Kolkata
005			20240923125845.0
008			210118b ||||| |||| 00| 0 eng d
040			_aISI Library _bEnglish
082	0	4	_223rd. _a571.95 _bR595
100	1		_aSen, Rishika _eauthor
245	1	0	_aIn silico identification of toxins and their effect on host pathways: _bfeature extraction classification and pathway prediction/ _cRishika Sen
260			_aKolkata: _bIndian Statistical Institute, _c2021
300			_a272 pages,
502			_aThesis (Ph.D.) - Indian Statistical Institute, 2021
504			_aIncludes bibliography
505	0		_aIntroduction and Scope of the Thesis -- A Review on Host–Pathogen Interactions: Classification and Prediction -- PyPredT6: An Ensemble Learning-based System for Identification of Type VI Effector Proteins -- Cluster Quality-based Non-Reductional (CQNR) Oversampling Technique and Effector Protein Predictor Based on 3D Structure (EPP3D) of Proteins -- DeepT7: A Deep Neural Network System for Identification of Type VII Effector Proteins -- DeepT7: A Deep Neural Network System for Identification of Type VII Effector Proteins -- Boolean Logic-based Network Robustness Analyzer (BNRA) and Its Application to a System of Host-Pathogen Interactions -- Conclusions and Scope for Future Research
508			_aGuided by Prof. Rajat K. De
520			_aIdentification of toxins, which are either proteins or small molecules, from pathogens is of paramount importance due to their crucial role as first-line invaders infiltrating a host, often leading to infection of the host. These toxins can affect specific proteins, like enzymes that catalyze metabolic pathways, affect metabolites that form the basis of metabolic reactions, and prevent the progression of those pathways, or more generally they may affect the regular functioning of other proteins in signaling pathways in the host. In this regard, the thesis addresses the problem of identification of toxins, and the effect of perturbations by toxins on the host pathways based on three tasks: feature extraction, classification and pathway prediction. The thesis starts with in silico identification of such toxins in pathogens. This is followed by the analysis of the effect of toxins on various metabolic and signaling pathways of the host.
650		4	_aPhysiology and related subjects
650		4	_aDisease
650		4	_aToxicology
650		4	_aToxins
650		4	_aPathway prediction
856			_yFull text _uhttp://dspace.isical.ac.in:8080/jspui/handle/10263/7117
942			_2ddc _cTH
999			_c428024 _d428024