At SEQOME we work on Big Data generated from High throughput Omics technologies and churn them to valuable information. Big data requires large storage and huge computational requirements and we use the power of Cloud to store and efficiently analyze Gigabases of information.
We love working with multiple applications of Next Generation Sequencing and Predictive Biology. Our team works with the clients to provide tailored solution to the Life Scientist. We not only provide Analytics and Software but we also provide Corporate Training and Consultancy to our clients.

Founder’s Profile

Dr. Jai Mehta, PhD Bioinformatics from Dublin City University specialize in Bioinformatics, Biostatistics and Computational Systems Biology. He has 15 years experience working with high throughput Omics, Systems Biology and Clinical datasets. His interest include Genomics, Transcriptomics and Proteomics and have worked on Next Generation Sequencing, Microarrays and Mass Spec dataset for multiple applications and developed techniques for data integration and visualization. Besides, he has a strong interest in Predictive Biology, Personalized medicine, Big data analytics and Cloud computing. He has developed software and algorithms for class prediction involving Neural Networks and Support Vector Machines. Dr Jai Prakash Mehta has also contributed to 30 publications including 5 books chapter and has presented his research in multiple conferences.

1. Duffy DJ, Krstic A, Halasz M, Schwarzl T, Fey D, Iljin K, Mehta JP, Killick K, Whilde J, Turriziani B, Haapa-Paananen S, Fey V, Fischer M, Westermann F, Henrich KO, Bannert S, Higgins DG, Kolch W. Integrative omics reveals MYCN as a global suppressor of cellular signalling and enables network-based therapeutic target discovery in neuroblastoma. Oncotarget. 2015 Dec 11. doi: 10.18632/oncotarget.6568. IF 6.4 [Pubmed]
2. Ahmed AM, Good B, Hanrahan JP, McGettigan P, Browne J, Keane OM, Bahar B, Mehta JP, Markey B, Lohan A, Sweeney T. Variation in the Ovine Abomasal Lymph Node Transcriptome between Breeds Known to Differ in Resistance to the Gastrointestinal Nematode. PLoS One. 2015 May 15;10(5):e0124823. doi: 10.1371/journal.pone.0124823. eCollection 2015. IF 3.2 [Pubmed]
3. Farrell J1, Kelly C, Rauch J, Kida K, García-Muñoz A, Monsefi N, Turriziani B, Doherty C, Mehta JP, Matallanas D, Simpson JC, Kolch W, von Kriegsheim A. HGF induces epithelial-to-mesenchymal transition by modulating the mammalian hippo/MST2 and ISG15 pathways. J Proteome Res. 2014 Jun 6;13(6):2874-86. doi: 10.1021/pr5000285. Epub 2014 May 5. [Pubmed]
4. Okumu LA, Forde N, Mamo S, McGettigan PA, Mehta JP, Roche JF, Lonergan P. Temporal regulation of fibroblast growth factors in the bovine endometrium and conceptus. Reproduction. 2014 Feb 19. [Epub ahead of print] IF 3.55 [Pubmed]
5. Forde N, McGettigan PA, Mehta JP, O’Hara L, Mamo S, Bazer FW, Spencer TE, Lonergan P. Proteomic analysis of uterine fluid during the pre-implantation period of pregnancy in cattle. Reproduction. 2014 Apr 8;147(5):575-87. doi: 10.1530/REP-13-0010. Print 2014. IF 3.55 [PubMed]
6. Forde N, Mehta JP, McGettigan PA, Mamo S, Bazer FW, Spencer TE, Lonergan P. Alterations in expression of endometrial genes coding for proteins secreted into the uterine lumen during conceptus elongation in cattle. BMC Genomics. 2013 May 10;14:321. doi: 10.1186/1471-2164-14-321. IF 4.07 [PubMed]
7. Forde N, Carter F, di Francesco S, Mehta JP, Garcia-Herreros M, Gad AY, Tesfaye D, Hoelker M, Schellander K, Lonergan P. Endometrial response of beef heifers on Day 7 following insemination to supra-physiological concentrations of progesterone associated with superovulation. Physiol Genomics. 2012 Nov 16;44(22):1107-15. IF: 2.74 [PubMed]
8. Forde N, Mehta JP, Minten M, Crowe MA, Roche JF, Spencer TE, Lonergan P. Effects of Low Progesterone on the Endometrial Transcriptome in Cattle. Biol Reprod. 2012 Nov 29;87(5):124. IF: 4.009 [PubMed]
9. Forde N, Duffy GB, McGettigan PA, Browne JA, Mehta JP, Kelly AK, Mansouri-Attia N, Sandra O, Loftus BJ, Crowe MA, Fair T, Roche JF, Lonergan P, Evans AC. Evidence for an early endometrial response to pregnancy in cattle: both dependent upon and independent of interferon tau. Physiol Genomics. 2012 Aug 17;44(16):799-810. Epub 2012 Jul 3 IF: 2.74 [PubMed]
10. Mamo S, Mehta JP, Forde N, McGettigan P, Lonergan P. Conceptus-Endometrium Crosstalk During Maternal Recognition of Pregnancy in Cattle. Biol Reprod. 2012 Jul 5;87(1):6, 1-9 IF: 4.009 [PubMed]
11. Walsh SW, Mehta JP, McGettigan PA, Browne JA, Forde N, Alibrahim R, Mulligan F, Loftus B, Crowe MA, Matthews D, Diskin MG, Mihm M, Evans AC Effect of the metabolic environment at key stages of follicle development in cattle: focus on steroid biosynthesis. Physiological Genomics. 2012 May 2;44(9):504-17 IF: 2.74 [PubMed]
12. O’Shea LC, Mehta JP, Lonergan P, Hensey C, Fair T. Developmental competence in oocytes and cumulus cells: candidate genes and networks. Systems Biology in Reproductive Medicine. 2012 Apr;58(2):88-101. IF: 1.52 [PubMed]
13. Mamo S, Mehta JP, McGettigan P, Fair T, Spencer TE, Bazer FW, Lonergan P. RNA Sequencing Reveals Novel Gene Clusters in Bovine Conceptuses Associated with Maternal Recognition of Pregnancy and Implantation . Biology of Reproduction. 2011 Dec;85(6):1143-51. IF: 4.009 [PubMed]
14. Clemente M, Lopez-Vidriero I, O’Gaora P, Mehta JP, Forde N, Gutierrez-Adan A, Lonergan P, Rizos D. Transcriptome Changes at the Initiation of Elongation in the Bovine Conceptus. Biol Reprod. 2011 Aug;85(2):285-95. IF: 4.009 [PubMed]
15. Mamo S, Carter F, Lonergan P, Leal CL, Al Naib A, McGettigan P, Mehta JP, Evans AC, Fair T. Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation. BMC Genomics. 2011 Mar 16;12:151. IF 4.07 [PubMed]
16. Forde N, Carter F, Spencer TE, Bazer FW, Sandra O, Mansouri-Attia N, Okumu LA, McGettigan PA, Mehta JP, McBride R, O’Gaora P, Roche JF, Lonergan P. Conceptus-Induced Changes in the Endometrial Transcriptome: How Soon Does the Cow Know She Is Pregnant? Biology of Reproduction. 2011 Jul;85(1):144-56. IF: 4.009 [PubMed]
17. Forde N, Beltman ME, Duffy GB, Duffy P, Mehta JP, O’Gaora P, Roche JF, Lonergan P, Crowe MA. Changes in the Endometrial Transcriptome During the Bovine Estrous Cycle: Effect of Low Circulating Progesterone and Consequences for Conceptus Elongation. Biology of Reproduction. 2011 Feb;84(2):266-78. IF: 4.009 [PubMed]
18. F. Carter1, F. Rings, S. Mamo, Mehta JP, M. Hölker, A. Kuzmany, U. Besenfelder, V. Havlicek, D. Tesfaye, K. Schellander, P. Lonergan1. Effect of Elevated Circulating Progesterone Concentration on Bovine Blastocyst Development and Global Transcriptome Following Endoscopic Transfer of In Vitro Produced Embryos to the Bovine Oviduct. Biology of Reproduction. 2010 Nov;83(5):707-19. IF: 4.009 [PubMed]
19. Rani S, Mehta JP, Doolan P, Barron N, Jeppesen PB, Clynes M, O’Driscoll L: Decreasing Txnip mRNA and protein levels in pancreatic MIN6 cells reduces reactive oxygen species and restores glucose regulated insulin secretion: Cell Physiol Biochem 2010;25(6):667-674. IF: 3.56 [PubMed]
20. Doolan P, Clynes M, Kennedy S, Mehta JP, Germano S, Ehrhardt C, Crown J, O’Driscoll L. TMEM25, REPS2 and Meis 1: favourable prognostic and predictive biomarkers for breast cancer. Tumour Biology 2009;30:200–209. IF: 2.48 [PubMed]
21. Kennedy S, Clynes M, Doolan P, Mehta JP, Rani S, Crown J, O’Driscoll L.SNIP/p140Cap mRNA expression is an unfavourable prognostic factor in breast cancer and is not expressed in normal breast tissue. British Journal of Cancer 2008 May 20;98(10):1641-5. IF: 4.346 [PubMed]
22. O’Driscoll L, Kenny E, Mehta JP, Doolan P, Joyce H, Gammell P, Hill A, O’Daly B, O’Gorman D, Clynes M. Feasibility and relevance of global expression profiling of gene transcripts in serum from breast cancer patients using whole genome microarrays and quantitative rt-PCR. Cancer Genomics Proteomics. 2008 Mar-Apr;5(2):94-104.[PubMed]
23. Mehta JP, O’Driscoll L, Barron N, Clynes M, Doolan P. “A microarray approach to translational medicine in breast cancer: how representative are cell line models of clinical conditions?” Anticancer Res. 2007 May-Jun;27(3A):1295-300 IF 1.41 [PubMed]
24. Doolan P, Clynes M, Kennedy S, Mehta JP, Crown J, O’driscoll L. “Prevalence and prognostic and predictive relevance of PRAME in breast cancer.” Breast Cancer Res Treat. 2008 May;109(2):359-65. IF: 4.696 [PubMed]
25. O’Driscoll L, McMorrow J, Doolan P, McKiernan E, Mehta JP, Ryan E, Gammell P, Joyce H, O’Donovan N, Walsh N, Clynes M. “Investigation of the molecular profile of basal cell carcinoma using whole genome microarrays.” Mol Cancer. 2006 Dec 15;5:74. IF 4.16 [PubMed]

26. Martinez V, Kennedy S, Doolan P, Gammell P, Joyce H, Kenny E, Mehta JP, Ryan E, O’connor R, Crown J, Clynes M, O’driscoll L. Drug metabolism-related genes as potential biomarkers: analysis of expression in normal and tumour breast tissue. Breast Cancer Res Treat. 2008 Aug;110(3):521-30. IF=4.696 [PubMed]

Jai Prakash Mehta “Understanding Breast Cancer dynamics using Gene Expression Profiling” Lambert Academic publication. ISBN No: 978-3-8383-5931-1

Jai Prakash Mehta: “Sequencing small RNA: Introduction and Data Analysis Fundamentals” RNA Mapping. Methods and Protocols. Humana Press. Methods Mol Biol. 2014;1182:93-103. doi: 10.1007/978-1-4939-1062-5_9.

2. Jai Prakash Mehta: “Microarray analysis of mRNAs: Experimental design and data analysis fundamentals.” Gene Expression Profiling, Methods and Protocols. Humana Press. ISBN: 978-1617792885. [PubMed]
3. Jai Prakash Mehta and Sweta Rani: “Software and tools for microarray data analysis” Gene Expression Profiling, Methods and Protocols, Humana Press ISBN: 978-1617792885.[PubMed]

4. Jai Prakash Mehta, Lorraine O’Driscoll, Niall Barron, Martin Clynes and Padraig Doolan “Translating in vitro cell lines results into clinical practice” Methods of Cancer Diagnosis, therapy and prognosis Vol 7. Springer Publication. ISBN 978-90-481-3185-3

1. Jai Prakash Mehta. “Sequencing to Systems Biology”. International Symposium cum Training Workshop, On Recent Trends in Bioinformatics, Systems Biology and Biomolecular Interactions, Allahabad University. Jan 8-10, 2012.
2. Jai Prakash Mehta. “Self-Organizing maps and its application to Microarray Technology”, International symposium on Applied Artificial Intelligence, 2003, Kolhapur, India.
3. Jai Prakash Mehta and Sarah Thomas-Cherian. “Cancer classification using microarray gene expression data with a Backpropagation based Neural Network algorithm without feature selection”, International Symposium on Mathematical Biology, 2004, IIT Kanpur, India.
4. Sarah Cherian, Jai Prakash Mehta and P. B. Vidyasagar. “A back propagation Neural Network for eukaryotic Pol II promoter prediction, studies related to inter and intra species training”. International conference on Bioinformatics, 2002, Bangkok, Thailand.
5. Jai Prakash Mehta, David J. Duffy, Thomas Schwarzl and Walter Kolch. Sequencing approach to identify miRNA targets for MYCN over-expression. System Medicine International Conference, 10th-13th September, Dublin, Ireland.
6. Jai Prakash Mehta, Walter Kolch, Boris Kholodenko. Meta-analysis on IEG and DEG on cells stimulated with EGF. Welcome trust advance course: In-Silico systems Biology from 23-27 April 2012. Wellcome Trust Genome Campus, Hinxton, Cambridge, UK
7. Jai Prakash Mehta, Lorraine O’Driscoll, Niall Barron, Martin Clynes and Padraig Doolan. “Identifying clusters of functionally related transcripts using large scale gene expression analysis.” Critical Assessment of Microarray Data Analysis (CAMDA 2007), Valencia, Spain 2007.
8. Jai Prakash Mehta, Padraig Doolan, Martin Clynes. “How Representative are Cell line models to clinical conditions? A microarray approach to translational medicine in breast cancer.” Global mRNA and Protein Expression Analysis 2006, Dublin, Ireland.
9. Jai Prakash Mehta, Padraig Doolan, Niall Barron, Lorraine O’Driscoll and Martin Clynes. “Meta-analysis of estrogen receptor-positive breast cancer data obtained from publicly available large scale Gene Expression analysis” INCOB 2006, New Delhi.

10. Jai Prakash Mehta, Martin Clynes, Dr. (Mrs.) Sarah Cherian. “Machine Learning for accurate cancer classification” Bioinformatics International Workshop and Symposium, 2005, Dublin, Ireland.

Amlendu Kumar has over 20 Years’ experience in Software Design, Development and Deployment. He has extensive experience working on multiple platforms including Multiple Database platforms, JAVA, NET and LAMP technologies. Currently he is working on Big Data Analytics and Software development on Cloud Platform. His expertise also includes LIMS architecture design and development, Machine Integration, Analytics Automation and seamless integration with Cloud platforms.


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