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Your search keyword '"Chirag N. Patel"' showing total 3 results
Start Over Author "Chirag N. Patel" Publisher cold spring harbor laboratory
3 results on '"Chirag N. Patel"'

1. Real time scalable data acquisition of COVID-19 in six continents through PySpark - a big data tool

Author

Daxesh P. Patel, Tanvi S Patel, and Chirag N. Patel

Subjects
Coronavirus disease 2019 (COVID-19), Computer science, business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Big data, Python (programming language), Data science, Data acquisition, Spark (mathematics), Pandemic, Scalability, business, computer, computer.programming_language
Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was declared as a global emergency in January 2020 due to its pandemic outbreak. To examine this Coronavirus disease 2019 (COVID-19) effects various data are being generated through different platforms. This study was focused on the clinical data of COVID-19 which relied on python programming. Here, we proposed a machine learning approach to provide a insights into the COVID-19 information. PySpark is a machine learning approach which also known as Apache spark an accurate tool for the searching of results with minimum time intervals as compare to Hadoop and other tools. World Health Organization (WHO) started gathering corona patients’ data from last week of the February 2020. On March 11, 2020, the WHO declared COVID-19 a global pandemic. The cases became more evident and common after mid-March. This paper used the live owid (our world in data) dataset and will analyse and find out the following details on the live COVID-19 dataset. (1) The daily Corona virus scenario on various continents using PySpark in microseconds of Processor time. (2) After the various antibodies have been implemented, how they impact new cases on a regular basis utilizing various graphs. (3) Tabular representation of COVID-19 new cases in all the continents.

Published
2021
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2. In-Silico analysis reveals lower transcription efficiency of C241T variant of SARS-CoV-2 with host replication factors MADP1 and HNRNP-1

Author

Chirag N. Patel, Neelam M. Nathani, Shantanu Shukla, Minal Chaudhari, Sapna Mahera, Madhvi Joshi, Dhaval Patel, Zuber Saiyed, Chaitanya G. Joshi, and Armi Chaudhari

Subjects
Untranslated region, Five prime untranslated region, In silico, Computer applications to medicine. Medical informatics, Mutant, R858-859.7, Health Informatics, Genomics, Biology, medicine.disease_cause, Genome, Article, 5′UTR, Transcription (biology), medicine, skin and connective tissue diseases, Transcription factor, Zinc finger, Genetics, MADP1, MD simulations, Mutation, SARS-CoV-2, Protein-RNA complexes, C241T, hnRNP1, MMPBSA
Abstract

Novel severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has claimed more than 3.3 million lives worldwide and still counting. As per the GISAID database, the genomics of SARS-CoV-2 has been extensively studied, with more than 500 genome submissions per day. Out of several hotspot mutations within the SARS-CoV-2 genome, recent research has focused mainly on the missense variants. Moreover, significantly less attention has been accorded to delineate the role of the untranslated regions (UTRs) of the SARS-CoV-2 genome in the disease progression and etiology. One of the most frequent 5’ UTR variants in the SARS-CoV-2 genome is the C241T, with a global frequency of more than 95 %. In the present study, the effect of the C241T mutation has been studied with respect to the changes in RNA structure and its interaction with the host replication factors MADP1 Zinc finger CCHC-type and RNA-binding motif 1 (hnRNP1). The results obtained from molecular docking and molecular dynamics simulation indicated weaker interaction of C241T mutant stem-loops with the host transcription factor MADP1, indicating a reduced replication efficiency. The results are also correlated with increased recovery rates and decreased death rates of global SARS-CoV-2 cases.

Published
2020
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3. Prevalence, phenotype and architecture of developmental disorders caused by de novo mutation: The Deciphering Developmental Disorders Study

Author

Nicola S. Cooper, S Samant, H Purnell, Claire L. S. Turner, A Vandersteen, Alex Magee, Susan Tomkins, Louise C. Wilson, L Greenhalgh, IK Temple, Irina Colgiu, A Duncan, G Cross, Susan E. Holder, C Wragg, Deirdre E. Donnelly, Nadia Akawi, Linda Sneddon, Eamonn Sheridan, Wendy D Jones, I Ellis, David Bourn, Joanna Poulton, Ingrid Simonic, R Singzon, Lisa Bradley, Matthew E. Hurles, Meena Balasubramanian, Dominic J. McMullan, Trevor Cole, Gillian Roberts, J Thomson, Moira Blyth, G Hollingsworth, Neeti Ghali, Alex Henderson, Zara Skitt, E Roberts, G Woods, David Goudie, J Awada, Caroline Langman, U Anjum, Martin O. Pollard, Usha Kini, Stephen Clayton, J Burn, Daniel M Barrett, Vka Kumar, Angela E. Douglas, Natalie Canham, Ruth Armstrong, Denise Williams, C Shaw-Smith, Lorraine Gaunt, S Ingram, Edward Blair, K Brunstrom, O. W.J. Quarrell, Ben Hutton, Nora Shannon, S Wallwark, Laura E Mason, Sarah F. Smithson, Jeremy F. McRae, Amanda L. Collins, Shane McKee, Katrina Prescott, Lara Cresswell, Sofia Douzgou, L Islam, C Deshpande, J Waters, Anna Middleton, S-M Park, Tarjinder Singh, Liu He, M Tein, T Fendick, B Kaemba, Tara Montgomery, Michael Wright, Jenny Morton, J Roberts, Emma Hobson, Caroline Mackie Ogilvie, Katrina Tatton-Brown, Lucy Jenkins, A Coates, Abhijit Dixit, Deborah J. Shears, Kath Smith, D. Baty, D Lim, D Cilliers, Richard Gibbons, Ruth Newbury-Ecob, M Squires, Nicola K. Ragge, Anneke Seller, E Kivuva, Kay Metcalfe, Fiona Stewart, K Marks, Elisabeth Rosser, R Fisher, Andrew E. Fry, Joan Paterson, Diana Wellesley, Dian Donnai, Christopher P. Bennett, Jonathan Berg, Ganesh J. Swaminathan, Lucy Raymond, Sally Ann Lynch, Pradeep C. Vasudevan, Rosemarie Davidson, Melita Irving, John Dean, Margo Whiteford, Melissa Lees, S Payne, K-R Ong, Emma Gray, M Holder, Dragana Josifova, Claire Kirk, McConnell, Helen Cox, Sarju G. Mehta, Elena Prigmore, Emma Shearing, Anand Saggar, Angela Barnicoat, Alejandro Sifrim, Nicola Foulds, Katherine Martin, Joanna Kaplanis, Sahar Mansour, Kirsty Ambridge, Clowes, A Procter, Z Miedzybrodzka, Katherine Lachlan, S Schweiger, E Maher, Allyson Ross, Simon Brent, C Sequeira, Tabib Dabir, Netravathi Krishnappa, Andrew Smith, B Bernhard, Andrew Green, Sara Widaa, Daniel A. King, Astrid Weber, Harinder Gill, Frances Flinter, Ruth McGowan, Siddharth Banka, Susan E. McNerlan, Elizabeth M. Sweeney, L Nevitt, Michael Parker, Hood Mugalaasi, AP Bevan, L Harrison, Varghese, Lucy Hildyard, Murday, G Kirby, S Clasper, Sutton, Clare Taylor, Andrew Jackson, A Selby, E Wilkinson, Miranda Splitt, Stuart Aitken, Shelagh Joss, Fiona Connell, Julie Vogt, Jill Clayton-Smith, Alan Fryer, N Pratt, Parthiban Vijayarangakannan, Shehla Mohammed, Susan Price, Wayne Lam, Peter D. Turnpenny, C Tysoe, Raheleh Rahbari, Marc Tischkowitz, N Williams, Tessa Homfray, Maria Bitner-Glindzicz, Helen Murphy, Meriel M. McEntagart, Sian Ellard, M Ahmed, R O'Shea, Andrew R. Norman, Daniel Perrett, Harrison, Philip Greene, David Moore, R Hawkins, DT Pilz, FitzPatrick, P Batstone, Esther Kinning, Caroline F. Wright, Yanick J. Crow, Kate Chandler, C Donnelly, Leema Robert, Straub, Susan M. Gribble, Philip Jones, D de Vries, K Evans, Simon J. Davies, Diana Baralle, E Miles, Jeffrey C. Barrett, A Lampe, Joshua C. Randall, Bruce Castle, K McKay, D Rice, Becky Treacy, Richard H Scott, Rosemary Kelsell, Angela F. Brady, Julian R. Sampson, J Jarvis, Laura Yates, R Sandford, Hayley Archer, M Yau, Mohnish Suri, Caroline Pottinger, Dhavendra Kumar, R. Taylor, Alison Kraus, L Bourdon, Alan Donaldson, S Everest, S Kazembe, Sian Morgan, C Longman, Ingrid Scurr, Alison Male, Ajoy Sarkar, Helen Kingston, Emma McCann, Julie M. Phipps, Andrea H. Németh, A Pridham, D Bohanna, C Gardiner, Diana Johnson, Tomas W Fitzgerald, Eleni A. Chatzimichali, A Dobbie, Diana Rajan, Frances Elmslie, Mohsan Alvi, Pendaran Roberts, Bronwyn Kerr, M D'Alessandro, Elizabeth A. Jones, Simon Holden, U Maye, Helen V. Firth, J Rankin, H. Stewart, S Naik, Adrian Tivey, Chirag N. Patel, Tanya Bayzetinova, G Lowther, G Devlin, A Torokwa, DJ Bunyan, Judith A. Goodship, Sarah Hewitt, Emma Wakeling, Christoffer Nellåker, S Wilcox, Saba Sharif, MN Collinson, C Brewer, Jacqueline Eason, C McWilliam, Jane A. Hurst, Angus John Clarke, Mervyn Humphreys, and Stephen W. Hellens

Subjects
Genetics, 0303 health sciences, education.field_of_study, Genetic heterogeneity, Population, Biology, Phenotype, DNA sequencing, 03 medical and health sciences, 0302 clinical medicine, education, Indel, Gene, Exome, 030217 neurology & neurosurgery, Exome sequencing, 030304 developmental biology
Abstract

Individuals with severe, undiagnosed developmental disorders (DDs) are enriched for damaging de novo mutations (DNMs) in developmentally important genes. We exome sequenced 4,293 families with individuals with DDs, and meta-analysed these data with published data on 3,287 individuals with similar disorders. We show that the most significant factors influencing the diagnostic yield of de novo mutations are the sex of the affected individual, the relatedness of their parents and the age of both father and mother. We identified 94 genes enriched for damaging de novo mutation at genome-wide significance (P < 7 × 10−7), including 14 genes for which compelling data for causation was previously lacking. We have characterised the phenotypic diversity among these genetic disorders. We demonstrate that, at current cost differentials, exome sequencing has much greater power than genome sequencing for novel gene discovery in genetically heterogeneous disorders. We estimate that 42% of our cohort carry pathogenic DNMs (single nucleotide variants and indels) in coding sequences, with approximately half operating by a loss-of-function mechanism, and the remainder resulting in altered-function (e.g. activating, dominant negative). We established that most haplo insufficient developmental disorders have already been identified, but that many altered-function disorders remain to be discovered. Extrapolating from the DDD cohort to the general population, we estimate that developmental disorders caused by DNMs have an average birth prevalence of 1 in 213 to 1 in 448 (0.22-0.47% of live births), depending on parental age.AbbreviationsPTVProtein-Truncating VariantDNMDe Novo MutationDDDevelopmental DisorderDDDDeciphering Developmental Disorders study

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