CiteULike: jyuh's Mukhopadhyay

Causality and pathway search in microarray time series experiment.

Nitai D Mukhopadhyay — 2007-01-03T15:58:54-00:00

Bioinformatics (8 December 2006)

MOTIVATION: Interaction among time series can be explored in many ways. All the approach has the usual problem of low power and high dimensional model. Here we attempted to build a causality network among a set of time series. The causality has been established by Granger causality, and then constructing the pathway has been implemented by finding the Minimal Spanning Tree within each connected component of the inferred network. False discovery rate measurement has been used to identify the most significant causalities. RESULTS: Simulation shows good convergence and accuracy of the algorithm. Robustness of the procedure has been demonstrated by applying the algorithm in a non-stationary time series setup. Application of the algorithm in a real dataset identified many causalities, with some overlap with previously known ones. Assembled network of the genes reveals features of the network that are common wisdom about naturally occurring networks.

Proteasome-Independent Functions of Ubiquitin in Endocytosis and Signaling

Debdyuti Mukhopadhyay — 2007-01-13T17:01:08-00:00

Science, Vol. 315, No. 5809. (12 January 2007), pp. 201-205.

Ubiquitination is a reversible posttranslational modification of cellular proteins, in which a 76-amino acid polypeptide, ubiquitin, is primarily attached to the epsilon-amino group of lysines in target proteins. Ubiquitination is a major player in regulating a broad host of cellular processes, including cell division, differentiation, signal transduction, protein trafficking, and quality control. Aberrations in the ubiquitination system are implicated in pathogenesis of some diseases, certain malignancies, neurodegenerative disorders, and pathologies of the inflammatory immune response. Here, we discuss the proteasome-independent roles of ubiquitination in signaling and endocytosis. 10.1126/science.1127085

An improved algorithm for clustering gene expression data

Sanghamitra Bandyopadhyay — 2008-01-19T21:17:43-00:00

Bioinformatics, Vol. 23, No. 21. (1 November 2007), pp. 2859-2865.

Motivation: Recent advancements in microarray technology allows simultaneous monitoring of the expression levels of a large number of genes over different time points. Clustering is an important tool for analyzing such microarray data, typical properties of which are its inherent uncertainty, noise and imprecision. In this article, a two-stage clustering algorithm, which employs a recently proposed variable string length genetic scheme and a multiobjective genetic clustering algorithm, is proposed. It is based on the novel concept of points having significant membership to multiple classes. An iterated version of the well-known Fuzzy C-Means is also utilized for clustering. Results: The significant superiority of the proposed two-stage clustering algorithm as compared to the average linkage method, Self Organizing Map (SOM) and a recently developed weighted Chinese restaurant-based clustering method (CRC), widely used methods for clustering gene expression data, is established on a variety of artificial and publicly available real life data sets. The biological relevance of the clustering solutions are also analyzed. Contact: anirbanbuba@yahoo.com Supplementary information: The processed and normalized data sets, supplementary figures, tables and other related materials are available at http://d.1asphost.com/anirbanmukhopadhyay/simmts.html 10.1093/bioinformatics/btm418

Mega2: data-handling for facilitating genetic linkage and association analyses

Nandita Mukhopadhyay — 2005-05-19T18:11:29-00:00

Bioinformatics, Vol. 21, No. 10. (15 May 2005), pp. 2556-2557.

Simultaneous detection of apoptosis and mitochondrial superoxide production in live cells by flow cytometry and confocal microscopy.

P Mukhopadhyay — 2007-11-02T03:25:33-00:00

Nat Protoc, Vol. 2, No. 9. (2007), pp. 2295-2301.

Annexin V and Sytox Green are widely used markers to evaluate apoptosis in various cell types using flow cytometry and fluorescent microscopy. Recently, a novel fluoroprobe MitoSOX Red was introduced for selective detection of superoxide in the mitochondria of live cells and was validated for confocal microscopy and flow cytometry. This protocol describes simultaneous measurements of mitochondrial superoxide generation with apoptotic markers (Annexin V and Sytox Green) by both flow cytometry and confocal microscopy in endothelial cell lines. The advantages of the described flow cytometry method over other cell-based techniques are the tremendous speed (1-2 h), exquisite precision and the possibility of simultaneous quantitative measurements of mitochondrial superoxide generation and apoptotic (and other) markers, with maximal preservation of cellular functions. This method combined with fluorescent microscopy may be very useful to reveal important spatial-temporal changes in mitochondrial superoxide production and execution of programmed cell death in virtually any cell type.

Modification in reverse: the SUMO proteases.

D Mukhopadhyay — 2007-09-12T07:43:24-00:00

Trends Biochem Sci, Vol. 32, No. 6. (June 2007), pp. 286-295.

SUMOs (small ubiquitin-like modifiers) are ubiquitin-related proteins that become covalently conjugated to cellular target proteins that are involved in a variety of processes. Frequently, this modification has a key role in regulating the activities of those targets and, thus, their cellular functions. SUMO conjugation is a highly dynamic process that can be rapidly reversed by the action of members of the Ubl (ubiquitin-like protein)-specific protease (Ulp) family. The same family of enzymes is also responsible for maturation of newly synthesized SUMOs prior to their initial conjugation. Recent advances in structural, biochemical and cell biological analysis of Ulp/SENPs reveal their high degree of specificity towards SUMO paralogs, in addition to discrimination between processing, deconjugation and chain-editing reactions. The dissimilar sub-nuclear localization patterns of Ulp/SENPs and phenotypes of Ulp/SENP mutants further indicate that different Ulp/SENPs have distinct and non-redundant roles.

The role of the activin system in keloid pathogenesis.

A Mukhopadhyay — 2007-09-11T02:01:04-00:00

Am J Physiol Cell Physiol, Vol. 292, No. 4. (April 2007)

Keloid scars represent a pathological response to cutaneous injury under the regulation of many growth factors. Activin-A, a dimeric protein and a member of the transforming growth factor-beta superfamily, has been shown to regulate various aspects of cell growth and differentiation in the repair of the skin mesenchyme and the epidermis. Thus our aim was to study the role of activin and its antagonist, follistatin, in keloid pathogenesis. Increased mRNA expression for activin was observed in keloid scar tissue by performing RNase protection assay. Immunohistochemistry showed increased localization of both activin-A and follistatin in the basal layer of epidermis of keloid tissue compared with normal tissue. ELISA demonstrated a 29-fold increase in concentration of activin-A and an approximately 5-fold increase in follistatin in conditioned media in keloid fibroblasts compared with normal fibroblasts. Although keloid keratinocytes produced 25% more follistatin than normal keratinocytes, the amounts of activin-A, in contrast, was approximately 77% lower. Proliferation of fibroblasts was stimulated when treated with exogenous activin-A (46% increase in keloids fibroblasts) or following co-culture with hbetaAHaCaT cells (66% increase). Activin-A upregulated key extracellular matrix components, namely collagen, fibronectin, and alpha-smooth muscle actin, in normal and keloid fibroblasts. Co-treatment of follistatin with activin-A blocked the stimulatory effects of activin on extracellular matrix components. These findings emphasize the importance of the activin system in keloid biology and pathogenesis and suggest a possible therapeutic potential of follistatin in the prevention and treatment of keloids.