Member Profile
Membership type: full
Richa Naveed Ahamed
Country of origin: India Currently in: United Arab Emirates, Dubai General field of specialization: Medical and Health Sciences incl Neurosciences-
Degrees
2015 Doctorate Other -
Current Research Activities
Medical and Health Sciences incl Neurosciences
My current research is related to the following broad areas: Genomics Protein Structure Analysis Bioinformatics Biochemistry
Publications resulting from Research:
T. Richa, B. Zehra, A. Vijayakumar et al. Artificial intelligence and omics in malignant gliomas.Physiol Genomics. 2024; 56,12: 876-895.
T. Richa, B. Zehra, N. Sharon et al., Single-Cell Reconstruction and Mutation Enrichment Analysis Identifies
Dysregulated Cardiomyocyte and Endothelial Cells in Congenital Heart Disease. Physiol Genomics. 2023; 55(12):634-
646.
T. Richa, R. Abdel Hameid, A. Bankapur, et al. Single Cell Transcriptomics Trajectory and Molecular Convergence of Clinically Relevant Mutations in Brugada Syndrome. American Journal of Physiology-Heart and Circulatory Physiology 2021; 320(5):H1935-H1948.
N. Nasna*, T. Richa*, A. Bankapur, et al. Single-cell transcriptome identifies FCGR3B upregulated subtype of alveolar
macrophages in patients with critical COVID-19. Iscience. 2021; 24(9):103030.
*Equal contribution
N. Kosaji, B. Zehra, N. Nassir, T. Richa, R. Orszulak, A. R., Lim et al. Lack of ethnic diversity in single-cell transcriptomics hinders cell type detection and precision medicine inclusivity. Med. 2023, 4(4): 217-219.
N. Nasna*, T. Richa*, A. Bankapur, et al. Analyzing single cell transcriptome data from severe COVID-19 patients. STAR Protocols. 2022; 2(4):103030.
*Equal contribution
A.K. Rooj, E.Cormet-Boyaka, E.B. Clark, Y.J. Qadri, W.Lee, R. Boddu, A. Agarwal, T. Richa, M. Uddin, V.Parpura, E.J.Sorscher, C.M. Fuller and B.K. Berdiev. Association of cystic fibrosis transmembrane conductance regulator with epithelial sodium channel subunits carrying Liddle’s syndrome mutations. American Journal of Physiology-Lung cellular and molecular physiology 2021;321: L308-L32
G. Begum, A. Albanna, A. Bankapur, N. Nassir, T. Richa, B.K. Berdiev, H. Akter, N. Karuvantevida, B. Kellam, D. Alhashmi , W.W. Sung. Long-Read Sequencing Improves the Detection of Structural Variations Impacting Complex Non-Coding Elements of the Genome. International journal of molecular sciences 2021;22(4):2060.
T. Sivaraman and T. Richa. Cryptic intermediates and metastable states of proteins as predicted by OneG computational method. Journal of Biomolecular Structure and Dynamics 2021;18:1-6.
T. Richa, M Gentaro, M Taiji and Y. Kuroda. Large-scale all-atom molecular dynamics alanine-scanning of IAPP octapeptides provides insights into the molecular determinants of amyloidogenicity Scientific Reports 2019; 9: 2530.
T. Richa, S. Ide, R. Suzuki, T. Ebina and Y. Kuroda. Fast H-DROP: A thirty times accelerated version of H-DROP for interactive SVM-based prediction of helical domain linkers. Journal of Computer-Aided Molecular Design 2016; 31: 237-244.
D. P. Wankhede, M. Kumari, T. Richa, J. Aravind and S. Rajkumar. Genome wide identification and characterization of Calcium Dependent Protein Kinase gene family in Cajanus cajan. Journal of Environmental Biology 2017; 38: 169-177.
T. Richa and T. Sivaraman Computational analyses of cryptic intermediates in the native unfolding pathways of barnase and thioredoxin Biologia 2015; 70: 420-427.
T. Richa and T. Sivaraman. OneG-Vali: A Webserver for Detecting, Estimating and Validating Cryptic Intermediates of Proteins under Native Conditions. RSC Advances 2014; 4(69): 36325-36335.
D. Sivakumar, T. Richa, S. S. Rajesh, B. Gorai and T. Sivaraman. In silico methods for designing antagonists to anti-apoptotic members of bcl-2 family proteins. Mini-Reviews in Medicinal Chemistry 2012;12(11):1144-1153.
T. Richa and T. Sivaraman. OneG: A computational tool for predicting cryptic intermediates in the unfolding kinetics of proteins under native conditions. PLoS ONE 2012;7(3) e32465.
K. P. Rao*, T. Richa*, K. Kumar, B. Raghuram and A. K. Sinha. In silico analysis reveals 75 members of mitogen-activated protein kinase kinase kinase gene family in rice. DNA Research 2010;17(3):139-153.
*Equal contribution
Peter Brown, RELISH Consortium, Yaoqi Zhou. Large Expert-Curated Database for Benchmarking Document Similarity Detection in Biomedical Literature Search. Database 2019, 1-66
Y Banerjee, T. Richa, M Gholami, A Alsheikh-Ali, R Bayoumi, P Lansberg. Augmenting flexnerism via twitterism: need for integrating social media application in blueprinting pedagogical strategies for undergraduate medical education. JMIR medical education 5 (1), e12403
T. Richa, R Bayoumi, Lansberg P, Banerjee Y. Blending Gagne's Instructional Model with Peyton's Approach to Design an Introductory Bioinformatics Lesson-plan for Medical Students. JMIR Medical Education 2018. 4(2):e11122.
P. Arasu, T.Richa and T. Sivaraman. Review on Computational Methods for Predicting Residue-Specific Stabilities of Proteins. Journal of Pharmaceutical Sciences and Research 2015; 7(3): 159-162.
P. Das, T. Richa and T. Sivaraman. A computational strategy for predicting residue-specific stabilities of cardiotoxin III, an all β-sheet protein. Research Journal of Pharmaceutical, Biological and Chemical Sciences. 2014; 5(3): 1824-1831.
T. Richa and T. Sivaraman. Cooperative unfolding units and metastable states of cytochrome c551 from Pseudomonas aeruginosa under native conditions. Journal of Pharmaceutical Sciences and Research. 2014; 6(3):144-147.
T. Richa and T. Sivaraman. Structural stability and folding pathways of proteins under native conditions as monitored by hydrogen/deuterium (H/D) exchange methods. International Journal of Research in Pharmaceutical Sciences. 2013; 4(4): 550-562.
T. Richa and T. Sivaraman. CIntX: A software tool for calculating the intrinsic exchange rates of labile protons in proteins. Journal of Pharmaceutical Sciences and Research. 2012;4(6):1852-1858.
T. Richa and T. Sivaraman. META: A computational tool for predicting metastable states in the folding pathways of proteins. Journal of Pharmaceutical Sciences and Research. 2011;3(9):1486-1490.
T. Richa and T. Sivaraman. A novel algorithm for calculating intrinsic exchange rate constants of backbone amide protons in proteins. Proceedings of 2nd International Conference on Bioinformatics and System Biology (Editor-in-chief – M. Sabesan, Annamalai University; ISBN: 9788184352849), 2011, 89-94.
G. Khalique and T. Richa. A Survey of the Structural Parameters Used for Computational Prediction of Protein Folding Process. In: Shanker A. (eds) Bioinformatics: Sequences, Structures, Phylogeny. Springer, Singapore. 2018. Page 255-270. (BOOK CHAPTER)
Current profession
Current professional activities type:ResearchTeachingResearch and Teaching
Affiliations
RIKEN Center for Biosystems Dynamics Research (BDR), JAPAN -
Other Awards
Jun 2015JSPS Postdoctoral FellowJSPS Postdoctoral Fellowship provides an opportunity to conduct collaborative research for overseas researchers under the guidance of their hosts in universities in Japan. I was a Postdoctoral Fellow at Kuroda Lab, Tokyo University of Agriculture & Technology, Japan from June 2015 - May 2017, Structural bioinformatics has been my primary research area. I have successfully published my (postdoctoral work) results in the Journal of Computer-Aided Molecular Design (PMID:28028736) and also presented my work at various International conferences.Sep 20232023 PCGC/CDDRC FellowThe Pediatric Cardiac Genomics Consortium (PCGC) & Cardiovascular Development Data Resource Center (CDDRC) Fellows Program [funded by NIH] provides early-career researchers (graduate students, postdocs, junior faculty, and others) the opportunity to receive funding to help support research on novel and innovative data science and data-focused research problems in Congenital Heart Disease. Since its creation in 2009, the PCGC has explored the genetic underpinnings of CHD and has accumulated the largest collection, to date, of data and DNA from patients with CHD (>13,000 probands enrolled). https://benchtobassinet.com/?page_id=2686Sep 20242024 PCGC/CDDRC FellowThe Pediatric Cardiac Genomics Consortium (PCGC) & Cardiovascular Development Data Resource Center (CDDRC) Fellows Program [funded by NIH] provides early-career researchers (graduate students, postdocs, junior faculty, and others) the opportunity to receive funding to help support research on novel and innovative data science and data-focused research problems in Congenital Heart Disease. Since its creation in 2009, the PCGC has explored the genetic underpinnings of CHD and has accumulated the largest collection, to date, of data and DNA from patients with CHD (>13,000 probands enrolled). https://benchtobassinet.com/?page_id=2713Apr 20212021 Data Sciences International Physiological-Omics Trainee Research Excellence AwardThe Physiological-Omics Interest Group Trainee Research Excellence Award, presented by the American Physiological Society, honors outstanding trainees with the potential to make significant contributions to the scientific fields represented by the Physiological-Omics Group.
