Rajat De

Feature selection: a neuro-fuzzy approach

Proceedings of International Conference on Neural Networks (ICNN'96)

The feature evaluation index is defined as, ... 1 1 Skk&amp;amp;#x27;(f(&amp;amp;#x27;)) ... more The feature evaluation index is defined as, ... 1 1 Skk&amp;amp;#x27;(f(&amp;amp;#x27;)) = 2[/1Ck(f(P)) (1 - pck~(f(p)))] + 2[/&amp;amp;#x27;%k&amp;amp;#x27;(f(&amp;amp;#x27;)) (l - pck(f&amp;amp;#x27;pl))]. ... Note that, Sk is zero (minimum) if pck = 1 or 0, and is 0.25 (maximum) if pc, = 0.5. On the other hand, Skk&amp;amp;#x27; is zero (minimum) when pck = pck, = 1 or ...

GenSeg and MR-GenSeg: A novel segmentation algorithm and its parallel MapReduce based approach for identifying genomic regions with copy number variations

IEEE/ACM transactions on computational biology and bioinformatics, 2020

Identifying intragenic as well as intergenic sequences of the DNA, having structural alterations,... more Identifying intragenic as well as intergenic sequences of the DNA, having structural alterations, is a significantly important research area, since this may be the root cause of many neurological and autoimmune diseases, including cancer. Working with whole genome NGS data has provided a new insight in this regard, but has lead to huge explosion of data that is growing exponentially. Hence, the challenges lie in efficient means of storage and processing this big data. In this study, we have developed a novel segmentation algorithm, called GenSeg, and its parallel MapReduce based algorithm, called MR-GenSeg, for detecting copy number variations. In order to annotate CNVs (variants), segments formed by GenSeg/MR-GenSeg have been represented in a novel way using a binary tree, where each node is a CNV event. GenSeg considers each position specific data of whole genome DNA sequence, so that precise identification of breakpoints is possible. GenSeg/MR-GenSeg has been compared with twelve...

Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks

The 2006 IEEE International Joint Conference on Neural Network Proceedings

In this article we develop two connectionist models describing the dynamics of gene expression in... more In this article we develop two connectionist models describing the dynamics of gene expression incorporating protein concentration. The models are based on the theoretical study of Goutsias and Kim. We calculate the concentration of mRNAs and proteins at different time steps, and the concentrations of mRNAs and proteins are calculated as a function of step n. Here we consider concentration

ASAPP: Architectural Similarity-based Automated Pathway Prediction System and its Application in Host-Pathogen Interactions

IEEE/ACM Transactions on Computational Biology and Bioinformatics

The significance of metabolic pathway prediction is to envision the viable unknown transformation... more The significance of metabolic pathway prediction is to envision the viable unknown transformations that can occur provided the appropriate enzymes are present. It can facilitate the prediction of the consequences of host-pathogen interactions. In this article, we have proposed a new algorithm Architectural Similarity-based Automated Pathway Prediction (ASAPP) to predict metabolic pathways based on the structural similarity among the metabolites. ASAPP takes two-dimensional structure and molecular weight of metabolites as input, and generates a list of probable transformations without the knowledge of any externally established reactions, with an accuracy of 85.09 percent. ASAPP has also been applied to predict the outcome of pathogen liberated toxins on the carbohydrate and lipid pathways of the hosts. We have analyzed the disruption of host pathways in the presence of toxins, and have found that some metabolites in Glycolysis and the TCA cycle have a high chance of being the breakpoints in the pathway. The tool is available at http://asapp.droppages.com/.

ASAPP: Architectural Similarity-based Automated Pathway Prediction System and its Application in Host-Pathogen Interactions

The significance of metabolic pathway prediction is to envision the viable unknown transformation... more The significance of metabolic pathway prediction is to envision the viable unknown transformations that can occur provided the appropriate enzymes are present. It can facilitate the prediction of the consequences of host-pathogen interactions. In this article, we have proposed a new algorithm ASAPP (Architectural Similarity-based Automated Pathway Prediction) to predict metabolic pathways based on the structural similarity among the metabolites. ASAPP takes two-dimensional structure and molecular weight of metabolites as input, and generates a list of probable transformations without the knowledge of any externally established reactions, with an accuracy of 85.09%. ASAPP has also been applied to predict the outcome of pathogen liberated toxins on the carbohydrate and lipid pathways of the hosts. We have analyzed the disruption of host pathways in the presence of toxins, and have found that some metabolites in Glycolysis and the TCA cycle have a high chance of being the breakpoints i...

Modeling and Analyzing the Effects of Crosstalk in a Biochemical Pathway: A Study on Human mTOR Signaling Pathway

Current Bioinformatics, 2016

Obesity: An Immunometabolic Perspective

Frontiers in Endocrinology, 2016

Obesity, characterized by chronic activation of inflammatory pathways, is a critical factor contr... more Obesity, characterized by chronic activation of inflammatory pathways, is a critical factor contributing to insulin resistance (IR) and type 2 diabetes (T2D). Free fatty acids (FFAs) are increased in obesity and are implicated as proximate causes of IR and induction of inflammatory signaling in adipose, liver, muscle, and pancreas. Cells of the innate immune system produce cytokines, and other factors that affect insulin signaling and result in the development of IR. In the lean state, adipose tissue is populated by adipose tissue macrophage of the anti-inflammatory M2 type (ATM2) and natural killer (NK) cells; this maintains the insulin-sensitive phenotype because ATM2 cells secrete IL10. In contrast, obesity induces lipolysis and release of pro-inflammatory FFAs and factors, such as chemokine (C-C motif) ligand 2 (CCL2) and tumor necrosis factor alpha (TNF-α), which recruit blood monocytes in adipose tissue, where they are converted to macrophages of the highly pro-inflammatory M1-type (ATM1). Activated ATM1 produce large amounts of pro-inflammatory mediators such as TNF-α, interleukin-1β, IL-6, leukotriene B4, nitric oxide (NO), and resistin that work in a paracrine fashion and cause IR in adipose tissue. In the liver, both pro-inflammatory Kupffer cells (M1-KCs) and recruited hepatic macrophages (Ly6C high) contribute to decreased hepatic insulin sensitivity. The present mini-review will update the bidirectional interaction between the immune system and obesity-induced changes in metabolism in adipose tissue and liver and the metabolic consequences thereof.

Download

Precision medicine with electronic medical records: from the patients and for the patients

Annals of Translational Medicine, 2016

The ideas of incorporating individual variabilities for prevention and treatment of diseases are ... more

Proceedings of the 2nd international conference on Pattern recognition and machine intelligence

Learning weights representating enzyme concentration: identification of metabolic pathways

Generational PipeLined Genetic Algorithm (PLGA) using Stochastic Selection

Csse, 2010

In this paper, a pipelined version of genetic algorithm, called PLGA, and a corresponding hardwar... more In this paper, a pipelined version of genetic algorithm, called PLGA, and a corresponding hardware platform are described. The basic operations of conventional GA (CGA) are made pipelined using an appropriate selection scheme. The selection operator, used here, is stochastic in nature and is called SA-selection. This helps maintaining the basic generational nature of the proposed pipelined GA (PLGA). A number of benchmark problems are used to compare the performances of conventional roulette-wheel selection and the SA-selection. These include unimodal and multimodal functions with dimensionality varying from very small to very large. It is seen that the SA-selection scheme is giving comparable performances with respect to the classical roulette-wheel selection scheme, for all the instances, when quality of solutions and rate of convergence are considered. The speedups obtained by PLGA for different benchmarks are found to be significant. It is shown that a complete hardware pipeline can be developed using the proposed scheme, if parallel evaluation of the fitness expression is possible. In this connection a low-cost but very fast hardware evaluation unit is described. Results of simulation experiments show that in a pipelined hardware environment, PLGA will be much faster than CGA. In terms of efficiency, PLGA is found to outperform parallel GA (PGA) also.

Download

Deciphering the cause of evolutionary variance within intrinsically disordered regions in human proteins

Journal of Biomolecular Structure and Dynamics, 2016

Why the intrinsically disordered regions evolve within human proteome has became an interesting q... more Why the intrinsically disordered regions evolve within human proteome has became an interesting question for a decade. Till date it remains an unsolved yet an intriguing issue to investigate why some of the disordered regions evolve rapidly while the rest are highly conserved across mammalian species. Identifying the key biological factors, responsible for the variation in the conservation rate of different disordered regions within the human proteome, may revisit the above issue. We emphasized that among the other biological features (multifunctionality, gene essentiality, protein connectivity, number of unique domains, gene expression level and expression breadth) considered in our study, the number of unique protein domains acts as a strong determinant that negatively influences the conservation of disordered regions. In this context, we justified that proteins having a fewer types of domains preferably need to conserve their disordered regions to enhance their structural flexibility which in turn will facilitate their molecular interactions. In contrast, the selection pressure acting on the stretches of disordered regions is not so strong in the case of multi-domains proteins. Therefore, we reasoned that the presence of conserved disordered stretches may compensate the functions of multiple domains within a single domain protein. Interestingly, we noticed that the influence of the unique domain number and expression level acts differently on the evolution of disordered regions from that of well-structured ones.

Developmental Trend Derived from Modules of Wnt Signaling Pathways

Lecture Notes in Computer Science, 2011

In this paper, we deal with the idea of creating a developmental trend from Wnt signaling pathway... more In this paper, we deal with the idea of creating a developmental trend from Wnt signaling pathways of different species. Wnt signaling pathway is involved in many crucial biological processes including from early embryonic development to stem cell management at later stages. The pathway varies in topology and size for each species that gets reflected in its modules. A comparison among species-specific pathways, taking into account the modules and pathway structure (in terms of nodes and edges) will throw light on crucial turning points in the development of Wnt signaling pathway. Hence, 31 species-specific Wnt signaling pathways have been modularized by the Modularization algorithm already developed by the authors. The modules were compared among themselves to find the trend of development. The trend established conserved modules among these pathways.

Download

SAGPAR: structural grammar-based automated pathway reconstruction

Interdisciplinary sciences, computational life sciences, 2012

In-silico metabolic engineering is a very useful branch of systems biology for modeling, analysis... more In-silico metabolic engineering is a very useful branch of systems biology for modeling, analysis and prediction of various outcomes of metabolic pathways. It can also be used for detecting interactions and dynamics within a network. Various protocols have been proposed for modeling a pathway. But most of these protocols have various disadvantages and shortcomings with respect to automated pathway modeling and analysis. In the present article, we have proposed a novel algorithm for automated pathway reconstruction. We have also made a comparative study of our algorithm with other standard protocols and discussed its advantages over others. We present StructurAl Grammar-based automated PAthway Reconstruction (SAGPAR), a fast and robust algorithm that generates any metabolic pathway using some given structural representations of metabolites. Users can model any pathway based on some pre-required features that are asked as an input by the algorithm. The algorithm also takes into consid...

Developmental trend derived from modules of Wnt signaling pathways

In this paper, we deal with the idea of creating a developmental trend from Wnt signaling pathway... more In this paper, we deal with the idea of creating a developmental trend from Wnt signaling pathways of different species. Wnt signaling pathway is involved in many crucial biological processes including from early embryonic development to stem cell management at later stages. The pathway varies in topology and size for each species that gets reflected in its modules. A comparison among species-specific pathways, taking into account the modules and pathway structure (in terms of nodes and edges) will throw light on crucial turning points in the development of Wnt signaling pathway. Hence, 31 species-specific Wnt signaling pathways have been modularized by the Modularization algorithm already developed by the authors. The modules were compared among themselves to find the trend of development. The trend established conserved modules among these pathways.

Download

SAGPAR: Structural Grammar-based automated pathway reconstruction

In-silico metabolic engineering is a very useful branch of systems biology for modeling, analysis... more In-silico metabolic engineering is a very useful branch of systems biology for modeling, analysis and prediction of various outcomes of metabolic pathways. It can also be used for detecting interactions and dynamics within a network. Various protocols have been proposed for modeling a pathway. But most of these protocols have various disadvantages and shortcomings with respect to automated pathway modeling and analysis. In the present article, we have proposed a novel algorithm for automated pathway reconstruction. We have also made a comparative study of our algorithm with other standard protocols and discussed its advantages over others. We present StructurAl Grammar-based automated PAthway Reconstruction (SAGPAR), a fast and robust algorithm that generates any metabolic pathway using some given structural representations of metabolites. Users can model any pathway based on some pre-required features that are asked as an input by the algorithm. The algorithm also takes into considerations various thermodynamic thresholds and structural properties while modeling a pathway. The given algorithm has been tested on the standard pathway datasets of 25 pathways of Mycoplasma pneumoniae M129 and 24 pathways of Homo sapiens. The dataset is taken from KEGG and PubChem Compound data repositories. SAGPAR performs much better than some already present metabolic pathway analysis tools like Copasi, PHT, Gepasi, Jarnac and Path-A.

A Constraint Based Method for Optimization in Metabolic Pathways

Lecture Notes in Computer Science, 2009

The analysis of pathways in metabolic networks has become an important approach for understanding... more The analysis of pathways in metabolic networks has become an important approach for understanding metabolic systems. Constraintbased approaches recently brought new insight into our understanding of metabolism. Here we introduce a method for identifying optimal metabolic pathways. The method, generates data on reaction fluxes based on biomass conservation constraint and formulates constraints incorporating weighting coefficients corresponding to concentration of enzymes catalyzing the reactions. The effectiveness of the present method is demonstrated on the pentose phosphate pathway (PPP) in T. cruzi and on a large network of the plant polyamine pathway existing in the literature. A comparative study with the existing extreme pathway analysis (EPA) also forms a part of this investigation.

Download

Identification of Gene Regulatory Pathways: A Regularization Method

Lecture Notes in Computer Science, 2007

Network based pathways are emerging as an important paradigm for analysis of biological systems. ... more Network based pathways are emerging as an important paradigm for analysis of biological systems. In the present article, we introduce a new method for identifying a set of extreme regulatory pathways by using structural equations as a tool for modeling genetic networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. The effectiveness of the present method is demonstrated on two genetic networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation.

Download

Pattern Recognition and Machine Intelligence

Lecture Notes in Computer Science, 2013

Connectionist Modelling of Dynamics of Gene Expression and Reverse Engineering Gene Regulatory Networks

International Symposium on Neural Networks, 2006

In this article we develop two connectionist models describing the dynamics of gene expression in... more In this article we develop two connectionist models describing the dynamics of gene expression incorporating protein concentration. The models are based on the theoretical study of Goutsias and Kim. We calculate the concentration of mRNAs and proteins at different time steps, and the concentrations of mRNAs and proteins are calculated as a function of step n. Here we consider concentration

Uploads

Papers by Rajat De

Log In