Publications
Corresponding author ‘ * ‘
– Degroat, W., Abdelhalim, H., Patel, K., Mendhe, D., Zeeshan. S., & Ahmed, Z.* (2024). Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine. Scientific Reports. 14, 1. PMID: 38167627. (Nature).
– Ahmed, Z.*, Degroat, W., Abdelhalim, H., Saman, Z., & Fine, D. (2024). Deciphering genomic signatures associating human dental oral craniofacial diseases with cardiovascular diseases using machine learning approaches. Clinical Oral Investigations. 52 (28), 1436-3771. PMID: 38163819. (Springer Nature).
– Ahmed, Z.* (2024). Deciphering expression and variants in CVD genes among heart failure population for precision medicine. ESC Heart Failure. 11, 1, 606-609. PMID: 38131165. (Heart Failure Association of the European Society of Cardiology. Wiley).
– Degroat, W., Mendhe, D., Bhurasi, A., Abdelhalim, H., Saman, Z., & Ahmed, Z.* (2023). IntelliGenes: A novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles. Bioinformatics. 39, 12. btad755. PMID: 38096588. (Oxford).
– Mhatre, I., Abdelhalim H, Degroat, W., Ashok, S., Liang, B., & Ahmed, Z.* (2023). Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases. Scientific Reports. 13(1), 16769. PMID: 37798313. (Nature).
– Patel, K., Venkatesan, C., Abdelhalim, H., Saman, Z., Arima, Y., Linna-Kuosmanen, S., & Ahmed, Z.* (2023). Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility. Human Genomics. 17, 47. PMID: 37270590. (BMC, Springer Nature)
– Wable, R., Nair, A.S., Pappu, A., Pierre-Louis, W., Abdelhalim, H., Patel, K., Mendhe, D., Bolla, S., Mittal, S., & Ahmed, Z*. (2023). Integrated ACMG approved genes and ICD codes for the translational research and precision medicine. Database: The Journal of Biological Databases and Curation. 2023, baad033. PMID: 37195695. (Oxford).
– Venkat, V., Abdelhalim, H., Degroat, W., Saman. Z., & Ahmed, Z*. (2023). Implementing machine learning techniques at RNA-seq driven gene-expression data to investigate genes associated with HF, AF, and other CVDs, and predict disease with high accuracy. Genomics. 115, 2. PMID: 36813091. (Elsevier)
– Degroat, W., Venkat, V., Pierre-Louis, W., Abdelhalim, H., & Ahmed, Z*. (2023). Hygieia: AI/ML pipeline integrating healthcare and genomics data to investigate genes associated with targeted disorders and predict disease. Software Impacts. 100493. (Elsevier).
– Ahmed, Z.*, Zeeshan, S., Persaud, N., Abdelhalim, H., Degroat, W., Liang, B. (2023). Investigating genes associated with cardiovascular disease among heart failure patients for translational research and precision medicine. Clinical and Translational Discovery. 3:e206. (Wiley).
– Ahmed, Z*. Zeeshan, S., & Lee, D. (2023). Editorial: Artificial intelligence for personalized and predictive genomics data analysis. Frontiers in Genetics. 14:1162869. PMID: 36936434. (Frontiers)
– Abdelhalim, H., Hunter, R.M., Mendhe, D., DeGroat, W., Saman, Z., & Ahmed Z.* (2023). Role of GWAS, polygenic risk score, and AI/ML using big data for personalized treatment to the patients with CVD. Future Medicine AI. (Future Medicine).
– Vadapalli, S., Abdelhalim, H., Zeeshan, S., & Ahmed, Z*. (2022). Artificial intelligence & machine learning approaches using gene expression and variant data for personalized medicine. Briefings in Bioinformatics. 23(5), bbac191. PMID: 35595537. (Oxford)
– Ahmed Z*. (2022). Precision medicine with multi-omics strategies, deep phenotyping, and predictive analysis. Progress in Molecular Biology and Translational Science. Editor: David B. Teplow. Volume 190, Issue 1, Pages 101-125. ISBN 9780323997843, Academic Press. PMID: 36007996. (Elsevier)
– Berber, A., Abdelhalim, H., Zeeshan, S., Vadapalli, S., von-Oehsen, B., Yanamala, N., Sengupta, P., & Ahmed, Z*. (2022). RNA-seq driven expression analysis to investigate Cardiovascular disease genes with associated phenotypes among Atrial Fibrillation patients. Clinical and Translational Medicine. PMID: 35875838. (Wiley)
– Abdelhalim, H., Berber, A., Lodi, M., Jain, R., Nair, A., Pappu, A., Patel, K., Venkat, V., Venkatesan, C., Wable, R., Dinatale, M., Fu, A., Iyer, V., Kalove, I., Kleyman, M., Koutsoutis, J., Menna, D., Paliwal, M., Patel, N., Patel, T., Rafique, Z., Samadi, R., Varadhan, R., Bolla, S., Vadapalli, S., & Ahmed, Z*. (2022). Artificial Intelligence, Healthcare, Clinical-Genomics, and Pharmacogenomics Approaches in Precision Medicine. Section: Computational Genomics. Research Topic: Artificial Intelligence for Personalized and Predictive Genomics Data Analysis. Frontiers in Genetics. 13, 929736. PMID: 35873469. (Frontiers)
– Ahmed Z*. (2022). Multi-omics strategies for personalized and predictive medicine: past, current, and future translational opportunities. Emerging Topics in Life Sciences. PMID: 35234253. (Portland Press, Biochemical Society and the Royal Society of Biology)
– Ahmed Z*., Renart., E., & Zeeshan, S. (2022). Investigating underlying human immunity genes, implicated diseases, and their relationship with the COVID-19. Personalized Medicine. 19(3), 229-250. PMID: 35261286
– Ahmed, Z*., Zeeshan, S., & Liang, B. T. (2021). RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk Heart Failure patients. Human Genomics. 15, 67. PMID: 34774109. (BMC, Springer Nature, Human Genome Organization)
– Ahmed, Z*. (2021).Intelligent health system for investigation and consenting COVID-19 patients and precision medicine. Personalized Medicine. 18(6), 573–582. PMID: 34619976
– Ahmed, Z*., Renart., E., Mishra, D., & Zeeshan, S. (2021). JWES: A new pipeline for whole genome/exome sequence data processing, management, and gene-variant discovery, annotation, prediction, and genotyping. FEBS Open Bio. 11(9):2441-2452. PMID: 34370400. (Wiley, Federation of European Biochemical Societies)
– Ahmed, Z*., Renart, E. G., Zeeshan, S., & Dong, X. (2021). Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis. Human Genomics. 15(1), 37. PMID: 34174938. (BMC, Springer Nature, Human Genome Organization)
– Ahmed, Z*., Renart., E., & Zeeshan, S.(2021). Genomics pipelines to investigate susceptibility in whole genome and exome sequenced data for variant discovery, annotation, prediction, and genotyping. PeerJ Life and Environment. 9:e11724. PMID: 34395068. (PeerJ)
– Ahmed, Z*., Zeeshan, S., Foran, D. J., Kleinman, L. C., Wondisford, F. E., & Dong, XQ. (2021). Integrative Clinical, Genomics and Metabolomics Data Analysis for Mainstream Precision Medicine to Investigate COVID-19. BMJ Innovations. 7, 6-10. (BMJ)
– Ahmed, Z*. (2020). Practicing precision medicine with intelligently integrative clinical and multi-omics data analysis. Human Genomics. 14(1), 35. PMID: 33008459. (BMC, Springer Nature)
– Ahmed, Z*., Zeeshan, S., Mendhe, D., & Dong, X. (2020). Human gene and disease associations for clinical-genomics and precision medicine research. Clinical and Translational Medicine. 10(1), 297–318. PMID: 32508008. (Wiley)
– Ahmed, Z*., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database : the journal of biological databases and curation, 2020, baaa010. PMID: 32185396. (Oxford)
– Zeeshan, S., Xiong, R., Liang, B. T., & Ahmed, Z*. (2020). 100 Years of evolving gene-disease complexities and scientific debutants. Briefings in Bioinformatics. 21(3), 885–905. PMID: 30972412. (Oxford)
– Ahmed, Z*., Kim, M., & Liang, B. T. (2019). MAV-clic: management, analysis, and visualization of clinical data. JAMIA open. 2(1), 23–28. PMID: 31984341. (Oxford)
– Ahmed, Z*., Zeeshan, S., Xiong, R., & Liang, B. T. (2019). Debutant iOS app and gene-disease complexities in clinical genomics and precision medicine. Clinical and Translational medicine. 8(1), 26. PMID: 31586224. (Wiley)
– Ahmed, Z*., & Dandekar, T. (2018). MSL: Facilitating automatic and physical analysis of published sci-entific literature in PDF format. F1000Research. 4, 1453. PMID: 29721305. (Faculty of 1000)
– Ahmed, Z*., & Ucar, D. (2017). I-ATAC: Interactive pipeline tool for the management and pre-processing of ATAC-seq samples. PeerJ Life and Environment, 5:e4040. PMID: 29181276. (PeerJ)
– Ahmed, Z*., Saman, Z., & Dandekar, T. (2016). Mining Biomedical Images towards Valuable Information Retrieval in Biomedical and Life Sciences. Database: The Journal of Biological Databases and Curation, baw118. PMID: 27538578. (Oxford)
– Ahmed, Z*., Bolisetty, M., Saman, Z., Anguiano, E., Ucar, D. (2016). MAV-seq: An interactive platform for the Management, Analysis, and Visualization of Sequence Data. Human Genomics. PMID: 27294413. (BMC, Springer Nature, Human Genome Organization)
– Ahmed, Z*., Michel, M., Saman, Z., Dandekar, T., Mueller, M., & Fekete, A. (2015). Lipid-Pro: A computational lipid identification solution for untargeted lipidomics on data-independent acquisition tan-dem mass spectrometry platforms. Bioinformatics. 31, 1150-1153. PMID: 25433698. (Oxford)
– Ahmed, Z., Saman, Z., Huber, C., Hensel, M., Schomburg, D., Münch, R., Eylert, E., Eisenreich. W, & Dandekar, T. (2014). Isotopo Database and Tool for Facile Analysis and Management of Mass Isotopomer Data. Database: The Journal of Biological Databases and Curation. 2014. PMID: 25204646. (Oxford)
– Dandekar, T., Fieselmann, A., Saman, M., & Ahmed, Z. (2014). Software Applications toward Quantitative Metabolic Flux Analysis and Visualization. Briefings in Bioinformatics. 15, 91-107. PMID: 23142828. (Oxford)
– Ahmed, Z*., Zeeshan, S., & Dandekar, T. (2014). Developing sustainable software solutions for bioinformatics by the ” Butterfly” paradigm. F1000Research, 3, 71. PMID: 25383181. (Faculty of 1000)
– Ahmed, Z., Saman, Z., Huber, C., Hensel, M., Schomburg, D., Münch, R., Eisenreich. W, & Dandekar, T. (2013). Software LS-MIDA for efficient Mass Isotopomer Distribution Analysis. BMC Bioinformatics. 14: 218. PMID: 23837681. (BMC, Springer Nature)