T. S. Keshava Prasad
Yenepoya University
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Featured researches published by T. S. Keshava Prasad.
Nucleic Acids Research | 2006
T. S. Keshava Prasad; Renu Goel; Kumaran Kandasamy; Shivakumar Keerthikumar; Sameer Kumar; Suresh Mathivanan; Deepthi Telikicherla; Rajesh Raju; Beema Shafreen; Abhilash Venugopal; Lavanya Balakrishnan; Arivusudar Marimuthu; Sutopa Banerjee; Devi S. Somanathan; Aimy Sebastian; Sandhya Rani; Somak Ray; C. J. Harrys Kishore; Sashi Kanth; Mukhtar Ahmed; Manoj Kumar Kashyap; Riaz Mohmood; Y. L. Ramachandra; V. Krishna; B. Abdul Rahiman; S. Sujatha Mohan; Prathibha Ranganathan; Subhashri Ramabadran; Raghothama Chaerkady; Akhilesh Pandey
Human Protein Reference Database (HPRD—http://www.hprd.org/), initially described in 2003, is a database of curated proteomic information pertaining to human proteins. We have recently added a number of new features in HPRD. These include PhosphoMotif Finder, which allows users to find the presence of over 320 experimentally verified phosphorylation motifs in proteins of interest. Another new feature is a protein distributed annotation system—Human Proteinpedia (http://www.humanproteinpedia.org/)—through which laboratories can submit their data, which is mapped onto protein entries in HPRD. Over 75 laboratories involved in proteomics research have already participated in this effort by submitting data for over 15 000 human proteins. The submitted data includes mass spectrometry and protein microarray-derived data, among other data types. Finally, HPRD is also linked to a compendium of human signaling pathways developed by our group, NetPath (http://www.netpath.org/), which currently contains annotations for several cancer and immune signaling pathways. Since the last update, more than 5500 new protein sequences have been added, making HPRD a comprehensive resource for studying the human proteome.
Nature | 2014
Min Sik Kim; Sneha M. Pinto; Derese Getnet; Raja Sekhar Nirujogi; Srikanth S. Manda; Raghothama Chaerkady; Dhanashree S. Kelkar; Ruth Isserlin; Shobhit Jain; Joji Kurian Thomas; Babylakshmi Muthusamy; Pamela Leal-Rojas; Praveen Kumar; Nandini A. Sahasrabuddhe; Lavanya Balakrishnan; Jayshree Advani; Bijesh George; Santosh Renuse; Lakshmi Dhevi N. Selvan; Arun H. Patil; Vishalakshi Nanjappa; Aneesha Radhakrishnan; Samarjeet Prasad; Tejaswini Subbannayya; Rajesh Raju; Manish Kumar; Sreelakshmi K. Sreenivasamurthy; Arivusudar Marimuthu; Gajanan Sathe; Sandip Chavan
The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.
PLOS Biology | 2012
Hina Kalra; Richard J. Simpson; Hong Ji; Elena Aikawa; Peter Altevogt; Philip W. Askenase; Vincent C. Bond; Francesc E. Borràs; Xandra O. Breakefield; Vivian Budnik; Edit I. Buzás; Giovanni Camussi; Aled Clayton; Emanuele Cocucci; Juan M. Falcon-Perez; Susanne Gabrielsson; Yong Song Gho; Dwijendra K. Gupta; H. C. Harsha; An Hendrix; Andrew F. Hill; Jameel M. Inal; Guido Jenster; Eva-Maria Krämer-Albers; Sai Kiang Lim; Alicia Llorente; Jan Lötvall; Antonio Marcilla; Lucia Mincheva-Nilsson; Irina Nazarenko
Vesiclepedia is a community-annotated compendium of molecular data on extracellular vesicles.
Genome Biology | 2010
Kumaran Kandasamy; S. Sujatha Mohan; Rajesh Raju; Shivakumar Keerthikumar; Ghantasala S. Sameer Kumar; Abhilash Venugopal; Deepthi Telikicherla; Daniel J. Navarro; Suresh Mathivanan; Christian Pecquet; Sashi Kanth Gollapudi; Sudhir Gopal Tattikota; Shyam Mohan; Hariprasad Padhukasahasram; Yashwanth Subbannayya; Renu Goel; Harrys K.C. Jacob; Jun Zhong; Raja Sekhar; Vishalakshi Nanjappa; Lavanya Balakrishnan; Roopashree Subbaiah; Yl Ramachandra; B. Abdul Rahiman; T. S. Keshava Prasad; Jian Xin Lin; Jon C. D. Houtman; Stephen Desiderio; Jean-Christophe Renauld; Stefan N. Constantinescu
We have developed NetPath as a resource of curated human signaling pathways. As an initial step, NetPath provides detailed maps of a number of immune signaling pathways, which include approximately 1,600 reactions annotated from the literature and more than 2,800 instances of transcriptionally regulated genes - all linked to over 5,500 published articles. We anticipate NetPath to become a consolidated resource for human signaling pathways that should enable systems biology approaches.
Methods of Molecular Biology | 2009
T. S. Keshava Prasad; Kumaran Kandasamy; Akhilesh Pandey
Although high-throughput technologies used in biology have resulted in the accumulation of vast amounts of data in the literature, it is becoming difficult for individual investigators to directly benefit from this data because they are not easily accessible. Databases have assumed a crucial role in assimilating and storing information that could enable future discoveries. To this end, our group has developed two resources - Human Protein Reference Database (HPRD) and Human Proteinpedia - that provide integrated information pertaining to human proteins. These databases contain information on a number of features of proteins that have been discovered using various experimental methods. Human Proteinpedia was developed as a portal for community participation to annotate and share proteomic data using HPRD as the scaffold. It allows proteomic investigators to even share unpublished data and provides an effective medium for data sharing. As proteomic information reflects a direct view of cellular systems, proteomics is expected to complement other areas of biology such as genomics, transcriptomics, classical genetics, and chemical genetics in understanding the relationships among genome, gene functions, and living systems.
Proceedings of the National Academy of Sciences of the United States of America | 2008
Scott J. Dixon; Yaroslav Fedyshyn; Judice L. Y. Koh; T. S. Keshava Prasad; Charly Chahwan; Gordon Chua; Kiana Toufighi; Anastasija Baryshnikova; Jacqueline Hayles; Kwang-Lae Hoe; Dong-Uk Kim; Han-Oh Park; Chad L. Myers; Akhilesh Pandey; Daniel Durocher; Brenda Andrews; Charles Boone
Synthetic lethal genetic interaction networks define genes that work together to control essential functions and have been studied extensively in Saccharomyces cerevisiae using the synthetic genetic array (SGA) analysis technique (ScSGA). The extent to which synthetic lethal or other genetic interaction networks are conserved between species remains uncertain. To address this question, we compared literature-curated and experimentally derived genetic interaction networks for two distantly related yeasts, Schizosaccharomyces pombe and S. cerevisiae. We find that 23% of interactions in a novel, high-quality S. pombe literature-curated network are conserved in the existing S. cerevisiae network. Next, we developed a method, called S. pombe SGA analysis (SpSGA), enabling rapid, high-throughput isolation of genetic interactions in this species. Direct comparison by SpSGA and ScSGA of ∼220 genes involved in DNA replication, the DNA damage response, chromatin remodeling, intracellular transport, and other processes revealed that ∼29% of genetic interactions are common to both species, with the remainder exhibiting unique, species-specific patterns of genetic connectivity. We define a conserved yeast network (CYN) composed of 106 genes and 144 interactions and suggest that this network may help understand the shared biology of diverse eukaryotic species.
Nucleic Acids Research | 2014
Vishalakshi Nanjappa; Joji Kurian Thomas; Arivusudar Marimuthu; Babylakshmi Muthusamy; Aneesha Radhakrishnan; Rakesh K. Sharma; Aafaque Ahmad Khan; Lavanya Balakrishnan; Nandini A. Sahasrabuddhe; Satwant Kumar; Binit N Jhaveri; Kaushal Vinaykumar Sheth; Ramesh Kumar Khatana; Patrick G. Shaw; S. Srikanth; Premendu P. Mathur; Subramanian Shankar; Dindagur Nagaraja; Rita Christopher; Suresh Mathivanan; Rajesh Raju; Ravi Sirdeshmukh; Aditi Chatterjee; Richard J. Simpson; H. C. Harsha; Akhilesh Pandey; T. S. Keshava Prasad
Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.
Molecular & Cellular Proteomics | 2011
Dhanashree S. Kelkar; Dhirendra Kumar; Praveen Kumar; Lavanya Balakrishnan; Babylakshmi Muthusamy; Amit Kumar Yadav; Priyanka Shrivastava; Arivusudar Marimuthu; S. Anand; Hema Sundaram; Reena Kingsbury; H. C. Harsha; Bipin G. Nair; T. S. Keshava Prasad; Devendra Singh Chauhan; Kiran Katoch; Vishwa Mohan Katoch; Prahlad Kumar; Raghothama Chaerkady; Debasis Dash; Akhilesh Pandey
The genome sequencing of H37Rv strain of Mycobacterium tuberculosis was completed in 1998 followed by the whole genome sequencing of a clinical isolate, CDC1551 in 2002. Since then, the genomic sequences of a number of other strains have become available making it one of the better studied pathogenic bacterial species at the genomic level. However, annotation of its genome remains challenging because of high GC content and dissimilarity to other model prokaryotes. To this end, we carried out an in-depth proteogenomic analysis of the M. tuberculosis H37Rv strain using Fourier transform mass spectrometry with high resolution at both MS and tandem MS levels. In all, we identified 3176 proteins from Mycobacterium tuberculosis representing ∼80% of its total predicted gene count. In addition to protein database search, we carried out a genome database search, which led to identification of ∼250 novel peptides. Based on these novel genome search-specific peptides, we discovered 41 novel protein coding genes in the H37Rv genome. Using peptide evidence and alternative gene prediction tools, we also corrected 79 gene models. Finally, mass spectrometric data from N terminus-derived peptides confirmed 727 existing annotations for translational start sites while correcting those for 33 proteins. We report creation of a high confidence set of protein coding regions in Mycobacterium tuberculosis genome obtained by high resolution tandem mass-spectrometry at both precursor and fragment detection steps for the first time. This proteogenomic approach should be generally applicable to other organisms whose genomes have already been sequenced for obtaining a more accurate catalogue of protein-coding genes.
Molecular BioSystems | 2012
Renu Goel; H. C. Harsha; Akhilesh Pandey; T. S. Keshava Prasad
Human Protein Reference Database (HPRD) is a rich resource of experimentally proven features of human proteins. Protein information in HPRD includes protein-protein interactions, post-translational modifications, enzyme/substrate relationships, disease associations, tissue expression, and subcellular localization of human proteins. Although, protein-protein interaction data from HPRD has been widely used by the scientific community, its phosphoproteome data has not been exploited to its full potential. HPRD is one of the largest documentations of human phosphoproteins in the public domain. Currently, phosphorylation data in HPRD comprises of 95,016 phosphosites mapped on to 13,041 proteins. Additionally, enzyme-substrate reactions responsible for 5930 phosphorylation events were also documented. Significant improvements in technologies and high-throughput platforms in biomedical investigations led to an exponential increase of biological data and phosphoproteomic data in recent years. Human Proteinpedia, a community annotation portal developed by us, has also contributed to the significant increase in phosphoproteomic data in HPRD. A large number of phosphorylation events have been mapped on to reference sequences available in HPRD and Human Proteinpedia along with associated protein features. This will provide a platform for systems biology approaches to determine the role of protein phosphorylation in protein function, cell signaling, biological processes and their implication in human diseases. This review aims to provide a composite view of phosphoproteomic data pertaining to human proteins in HPRD and Human Proteinpedia.
Nucleic Acids Research | 2009
Kumaran Kandasamy; Shivakumar Keerthikumar; Renu Goel; Suresh Mathivanan; Nandini Patankar; Beema Shafreen; Santosh Renuse; Harsh Pawar; Y. L. Ramachandra; Pradip Kumar Acharya; Prathibha Ranganathan; Raghothama Chaerkady; T. S. Keshava Prasad; Akhilesh Pandey
Sharing proteomic data with the biomedical community through a unified proteomic resource, especially in the context of individual proteins, is a challenging prospect. We have developed a community portal, designated as Human Proteinpedia (http://www.humanproteinpedia.org/), for sharing both unpublished and published human proteomic data through the use of a distributed annotation system designed specifically for this purpose. This system allows laboratories to contribute and maintain protein annotations, which are also mapped to the corresponding proteins through the Human Protein Reference Database (HPRD; http://www.hprd.org/). Thus, it is possible to visualize data pertaining to experimentally validated posttranslational modifications (PTMs), protein isoforms, protein–protein interactions (PPIs), tissue expression, expression in cell lines, subcellular localization and enzyme substrates in the context of individual proteins. With enthusiastic participation of the proteomics community, the past 15 months have witnessed data contributions from more than 75 labs around the world including 2710 distinct experiments, >1.9 million peptides, >4.8 million MS/MS spectra, 150 368 protein expression annotations, 17 410 PTMs, 34 624 PPIs and 2906 subcellular localization annotations. Human Proteinpedia should serve as an integrated platform to store, integrate and disseminate such proteomic data and is inching towards evolving into a unified human proteomics resource.