Pankaj Kumar

Bio: Pankaj Kumar is an academic researcher from Indian Institute of Science. The author has contributed to research in topics: Medicine & Internal medicine. The author has an hindex of 20, co-authored 130 publications receiving 2213 citations. Previous affiliations of Pankaj Kumar include National Environment Agency & University of Adelaide.

A genome-wide RNAi screen reveals determinants of human embryonic stem cell identity

Abstract: The derivation of human ES cells (hESCs) from human blastocysts represents one of the milestones in stem cell biology. The full potential of hESCs in research and clinical applications requires a detailed understanding of the genetic network that governs the unique properties of hESCs. Here, we report a genome-wide RNA interference screen to identify genes which regulate self-renewal and pluripotency properties in hESCs. Interestingly, functionally distinct complexes involved in transcriptional regulation and chromatin remodelling are among the factors identified in the screen. To understand the roles of these potential regulators of hESCs, we studied transcription factor PRDM14 to gain new insights into its functional roles in the regulation of pluripotency. We showed that PRDM14 regulates directly the expression of key pluripotency gene POU5F1 through its proximal enhancer. Genome-wide location profiling experiments revealed that PRDM14 colocalized extensively with other key transcription factors such as OCT4, NANOG and SOX2, indicating that PRDM14 is integrated into the core transcriptional regulatory network. More importantly, in a gain-of-function assay, we showed that PRDM14 is able to enhance the efficiency of reprogramming of human fibroblasts in conjunction with OCT4, SOX2 and KLF4. Altogether, our study uncovers a wealth of novel hESC regulators wherein PRDM14 exemplifies a key transcription factor required for the maintenance of hESC identity and the reacquisition of pluripotency in human somatic cells.

Update of TTD: Therapeutic Target Database

Abstract: Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved and clinical trial drugs. Knowledge of these targets and corresponding drugs, particularly those in clinical uses and trials, is highly useful for facilitating drug discovery. Therapeutic Target Database (TTD) has been developed to provide information about therapeutic targets and corresponding drugs. In order to accommodate increasing demand for comprehensive knowledge about the primary targets of the approved, clinical trial and experimental drugs, numerous improvements and updates have been made to TTD. These updates include information about 348 successful, 292 clinical trial and 1254 research targets, 1514 approved, 1212 clinical trial and 2302 experimental drugs linked to their primary targets (3382 small molecule and 649 antisense drugs with available structure and sequence), new ways to access data by drug mode of action, recursive search of related targets or drugs, similarity target and drug searching, customized and whole data download, standardized target ID, and significant increase of data (1894 targets, 560 diseases and 5028 drugs compared with the 433 targets, 125 diseases and 809 drugs in the original release described in previous paper). This database can be accessed at http://bidd.nus.edu.sg/group/cjttd/TTD.asp.

Framework for real-time behavior interpretation from traffic video

Abstract: Video-based surveillance systems have a wide range of applications for traffic monitoring, as they provide more information as compared to other sensors. In this paper, we present a rule-based framework for behavior and activity detection in traffic videos obtained from stationary video cameras. Moving targets are segmented from the images and tracked in real time. These are classified into different categories using a novel Bayesian network approach, which makes use of image features and image-sequence-based tracking results for robust classification. Tracking and classification results are used in a programmed context to analyze behavior. For behavior recognition, two types of interactions have mainly been considered. One is interaction between two or more mobile targets in the field of view (FoV) of the camera. The other is interaction between targets and stationary objects in the environment. The framework is based on two types of a priori information: 1) the contextual information of the camera's FoV, in terms of the different stationary objects in the scene and 2) sets of predefined behavior scenarios, which need to be analyzed in different contexts. The system can recognize behavior from videos and give a lexical output of the detected behavior. It also is capable of handling uncertainties that arise due to errors in visual signal processing. We demonstrate successful behavior recognition results for pedestrian-vehicle interaction and vehicle-checkpost interactions.

RNAi screening reveals a large signaling network controlling the Golgi apparatus in human cells

Abstract: The Golgi apparatus has many important physiological functions, including sorting of secretory cargo and biosynthesis of complex glycans. These functions depend on the intricate and compartmentalized organization of the Golgi apparatus. To investigate the mechanisms that regulate Golgi architecture, we developed a quantitative morphological assay using three different Golgi compartment markers and quantitative image analysis, and performed a kinome- and phosphatome-wide RNAi screen in HeLa cells. Depletion of 159 signaling genes, nearly 20% of genes assayed, induced strong and varied perturbations in Golgi morphology. Using bioinformatics data, a large regulatory network could be constructed. Specific subnetworks are involved in phosphoinositides regulation, acto-myosin dynamics and mitogen activated protein kinase signaling. Most gene depletion also affected Golgi functions, in particular glycan biosynthesis, suggesting that signaling cascades can control glycosylation directly at the Golgi level. Our results provide a genetic overview of the signaling pathways that control the Golgi apparatus in human cells.

A comparative study of different color spaces for foreground and shadow detection for traffic monitoring system

Abstract: Segmenting foreground objects of interest in real time is an important step in many applications of video surveillance, vehicle tracking and traffic monitoring. Background subtraction is a method very often used to segment moving objects in image sequences. In this paper we present a fundamental unbiased study of different color spaces for detecting foreground objects and their shadows in image sequences. Different color spaces show different efficiency in detection of foreground objects and their shadows. This empirical study was done with the motivation of determining, which color space is best for foreground segmentation and shadow detection. This study of the quality of foreground and shadow detection as a function of color space is unique kind and especially relevant to color image sequences. Our study includes five color spaces "RGB", "XYZ". "YC/sub r/C/sub b/", "HSV" and the normalized "rgb". We use an empirically substantiated model of shadows formulate the detection scheme for each color space. We use a statistical technique to model the background pixels. The results are compared in terms of true detection, misses and false detection of pixels and also detection of the moving foreground objects as blobs. The results show that "YC/sub r/C/sub b/" is the best color space for optimal foreground and shadow detection.

STRING v9.1: protein-protein interaction networks, with increased coverage and integration

Abstract: Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

DrugBank 3.0: a comprehensive resource for ‘Omics’ research on drugs

Abstract: DrugBank (http://www.drugbank.ca) is a richly annotated database of drug and drug target information. It contains extensive data on the nomenclature, ontology, chemistry, structure, function, action, pharmacology, pharmacokinetics, metabolism and pharmaceutical properties of both small molecule and large molecule (biotech) drugs. It also contains comprehensive information on the target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, DrugBank has become widely used by pharmacists, medicinal chemists, pharmaceutical researchers, clinicians, educators and the general public. Since its last update in 2008, DrugBank has been greatly expanded through the addition of new drugs, new targets and the inclusion of more than 40 new data fields per drug entry (a 40% increase in data ‘depth’). These data field additions include illustrated drug-action pathways, drug transporter data, drug metabolite data, pharmacogenomic data, adverse drug response data, ADMET data, pharmacokinetic data, computed property data and chemical classification data. DrugBank 3.0 also offers expanded database links, improved search tools for drug–drug and food–drug interaction, new resources for querying and viewing drug pathways and hundreds of new drug entries with detailed patent, pricing and manufacturer data. These additions have been complemented by enhancements to the quality and quantity of existing data, particularly with regard to drug target, drug description and drug action data. DrugBank 3.0 represents the result of 2 years of manual annotation work aimed at making the database much more useful for a wide range of ‘omics’ (i.e. pharmacogenomic, pharmacoproteomic, pharmacometabolomic and even pharmacoeconomic) applications.

Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions

Abstract: Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living. This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments. The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP). Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the the next revolutionary technology in transforming the Internet into a fully integrated Future Internet. As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly. This paper presents a cloud centric vision for worldwide implementation of Internet of Things. The key enabling technologies and application domains that are likely to drive IoT research in the near future are discussed. A cloud implementation using Aneka, which is based on interaction of private and public clouds is presented. We conclude our IoT vision by expanding on the need for convergence of WSN, the Internet and distributed computing directed at technological research community.