Ahmet Ay

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aay

Ahmet Ay

Professor of Biology and Mathematics; Director of the Research Council; and Director of the Picker Interdisciplinary Science Institute

Department/Office Information

Biology, Mathematics
408 Ho Science Center
  • T 3:30pm - 4:30pm (408 Ho Science Center)
  • R 2:00pm - 4:00pm (408 Ho Science Center)

 

Ph.D. in Mathematics and Quantitative Biology, Michigan State University

  • Professor, 2023-Present, Departments of Biology and Mathematics, Colgate University
  • Associate Professor, 2016-2023, Departments of Biology and Mathematics, Colgate University
  • Courtesy Associate Professor, 2017-2018, CISE Dept., University of Florida
  • Assistant Professor, 2010-2016, Departments of Biology and Mathematics, Colgate University
  • Visiting Research Scholar, 2013-2014, CISE Dept., University of Florida

Systems Biology, Mathematical Biology, Bioinformatics, Mathematical Modeling, Machine Learning, Molecular Clocks, Human Diseases, Biological Regulatory Networks.

Teaching:
My teaching interests include Systems Biology, Bioinformatics, Modeling of Biological Systems, Biostatistics, Numerical Analysis, Linear Algebra and Calculus.

Research:
My research interests fall into three categories: (1) Mathematical modeling of biological systems, including molecular clocks. (2) Applications of statistical learning to human diseases such as mood disorders. (3) Creation of bioinformatics methods and software.

Student research:
My lab's research focuses on using mathematical modeling, machine learning, and computer programming to understand better biological systems and human diseases. I've supervised over 80 research students from diverse backgrounds (e.g., Computer Science, Mathematics, and Biology) since 2010. More than 25 research students contributed to the publication of over 15 articles. Additionally, my students delivered research presentations at national and international conferences. More than 20 former research students now work for companies like Google, Facebook, Square, and Illumina, and more than 20 students are pursuing Ph.D., M.D., or M.S. degrees at Columbia, Harvard, Yale, UCLA, UCSD, and the University of Chicago.

* = Undergraduate Student Authors Mentored by Dr. Ay

Journal papers:

Russel, W.*, Perry, J.*, Bonzani, C.*, Dontino, A., Mekonnen, Z.,  Ay, A. & Taye, B. (2023). Feature Selection and Association rule learning Identify Risk Factors of Malnutrition Among Ethiopian Schoolchildren. Frontiers in Epidemiology, 3: 1150619.

Wang, D.*, Russel, W. A.*, Sun, Y.*, Belanger, K. D., & Ay, A. (2023). Machine learning and network analysis of the gut microbiome from patients with schizophrenia and non-psychiatric subject controls reveal behavioral risk factors and bacterial interactions. Schizophrenia Research, 251, 49-58.

Jimenez, A. G., Paul, K., Zafar, A.*, & Ay, A. (2023). Effect of different masses, ages, and coats on the thermoregulation of dogs before and after exercise across different seasons. Veterinary Research Communications, 47(2), 833-847.

Overton, R., Zafar, A.*, Attia, Z.*, Ay, A., & Ingram, K. K. (2022). Machine Learning Analyses Reveal Circadian Features Predictive of Risk for Sleep Disturbance. Nature and Science of Sleep, 1887-1900.

Dhawka, L., Cha, Y.*, Ay, A., Ingram, K.K. (2022). Low circadian amplitude and delayed phase are linked to Seasonal Affective Disorder (SAD).  Journal of Affective Disorders Reports, p.100395.

Tran, V.*, Saad, T.*, Tesfaye, M., Walelign, S., Wordofa, M., Abera, D., Desta, K., Tsegaye, A., Ay, A., & Taye, B. (2022). Helicobacter pylori (H. pylori) risk factor analysis and prevalence prediction: a machine learning-based approach. BMC Infectious Diseases, 22(1), pp.1-14.

Zinani, O. Q., Keseroglu, K., Dey, S., Ay, A., Singh, A., & Ozbudak, E. M. (2022). Gene copy number and negative feedback differentially regulate transcriptional variability of segmentation clock genes. iScience, 25(7), 104579.

Zafar, A.*, Attia, Z.*, Tesfaye, M., Walelign, S., Wordofa, M., Abera, D., Desta, K., Tsegaye, A., Ay, A., & Taye, B. (2022). Machine learning-based risk factor analysis and prevalence prediction of intestinal parasitic infections using epidemiological survey data. PLoS Neglected Tropical Diseases, 16(6), e0010517.

Birenbaum, Z.*, Do, H.*, Horstmyer, L., Orff, H., Ingram, K., & Ay, A. (2022). SEALNET: Facial recognition software for ecological studies of harbor seals.  Ecology and Evolution, 12(5), e8851.

Zafar, A.*, Overton, R., Attia, Z.*, Ay, A., & Ingram, K. (2022). Machine learning and expression analyses reveal circadian clock features predictive of anxiety.  Scientific Reports, 12(1), 1-11.

Ren, Y., Sarkar, A., Veltri, P., Ay, A., Dobra, A., & Kahveci, T. (2021). Pattern discovery in multilayer networks.  IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(2), 741-752.

Zinani, O. Q., Keseroğlu, K., Ay, A., & Özbudak, E. M. (2021). Pairing of segmentation clock genes drives robust pattern formation.  Nature, 589(7842), 431-436.

Chow, K.*, Sarkar, A., Elhesha, R., Cinaglia, P., Ay, A., & Kahveci, T. (2019). ANCA: Alignment-Based Network Construction Algorithm.  IEEE/ACM Transactions on Computational Biology and Bioinformatics, 18(2), 512-524.

Ren, Y., Ay, A., Dobra, A., & Kahveci, T. (2019). Characterizing building blocks of resource constrained biological networks.  BMC Bioinformatics, 20(12): 318.

Keskin, S., Simsek, M. F., Vu, H. T.*, Yang, C.*, Devoto, S. H., Ay, A., & Özbudak, E. M. (2019). Regulatory network of the scoliosis-associated genes establishes rostrocaudal patterning of somites in zebrafish.  iScience, 12, 247-259.

Ren, Y., Ay, A., & Kahveci, T. (2018). Shortest path counting in probabilistic biological networks.  BMC Bioinformatics, 19(1), 465.

Ren, Y., Ay, A., Gerke, T. A., & Kahveci, T. (2018). Identification of jointly correlated gene sets.  Journal of Bioinformatics and Computational Biology, 16(05), 1840019.

Keskin, S., Devakanmalai, G. S., Kwon, S. B.*, Vu, H. T.*, Hong, Q., Lee, Y. Y., Soltani, M., Singh, A., Ay, A., & Özbudak, E. M. (2018). Noise in the vertebrate segmentation clock is boosted by time delays but tamed by notch signaling.  Cell Reports, 23(7), 2175-2185.

Liberman, A. R.*, Halitjaha, L.*, Ay, A., & Ingram, K. K. (2018). Modeling strengthens molecular link between circadian polymorphisms and major mood disorders.  Journal of Biological Rhythms, 33(3), 318-336.

Alim, M. A., Ay, A., Hasan, M. M., Thai, M. T., & Kahveci, T. (2017). Construction of Signaling Pathways with RNAi Data and Multiple Reference Networks.  IEEE/ACM Transactions on Computational Biology and Bioinformatics, 15(4), 1079-1091.

Zaifman, J.*, Shan, D.*, Ay, A., & Jimenez, A. G. (2017). Shifts in bird migration timing in North American long-distance and short-distance migrants are associated with climate change.  International Journal of Zoology, 6025646.

Liberman, A. R.*, Kwon, S. B.*, Vu, H. T.*, Filipowicz, A., Ay, A., & Ingram, K. K. (2017). Circadian clock model supports molecular link between PER3 and human anxiety.  Scientific Reports, 7(1), 1-10.

Armstrong, G. W.*, Mahmood, A.*, Nugent, A., Dexter, S., Hutto, E., McCay, T. S., Ay, A. (2017) WORMSPREAD: an individual-based model of invasive earthworm population dynamics.  Computational Ecology and Software 7(3): 109-122.

Yildirim, N., Aktas, M. E., Ozcan, S. N., Akbas, E., & Ay, A. (2017). Differential transcriptional regulation by alternatively designed mechanisms: A mathematical modeling approach.  In Silico Biology, 12(3-4), 95-127.

Ren, Y., Wang, Q., Hasan, M. M., Ay, A., & Kahveci, T. (2016). Identifying the topology of signaling networks from partial RNAi data.  BMC Systems Biology, 10(2), 231-242.

Ingram, K. K., Ay, A., Kwon, S. B.*, Woods, K., Escobar, S., Gordon, M., Smith I., Bearden I., Filipowicz A., & Jain, K. (2016). Molecular insights into chronotype and time-of-day effects on decision-making.  Scientific Reports, 6(1), 1-9.

Belanger, K. D., Larson, N.*, Kahn, J.*, Tkachev, D., & Ay, A. (2016). Mutant screen report: Microarray analysis of gene expression in  S. cerevisiae  kap108Delta mutants upon addition of oxidative stress.  G3: Genes, Genomes, Genetics, 6(4), 1131-1139.

Kok, K., Ay, A., Li, L. M., & Arnosti, D. N. (2015). Genome-wide errant targeting by Hairy.  eLife, 4, e06394.

Ferrante, A., Gellerman, D., Ay, A., Woods, K. P., Filipowicz, A. M., Jain, K., Jain K., Bearden N., & Ingram, K. K. (2015). Diurnal preference predicts phase differences in expression of human peripheral circadian clock genes.  Journal of Circadian Rhythms, 13(4), 1-7. 

Ay, A., Wilner, N.*, & Yildirim, N. (2015). Mathematical modeling deciphers the benefits of alternatively-designed conserved activatory and inhibitory gene circuits.  Molecular BioSystems, 11(7), 2017-2030.

Ay, A., Gong, D., & Kahveci, T. (2015). Hierarchical decomposition of dynamically evolving regulatory networks.  BMC Bioinformatics, 16(1), 1-19.

Ay, A., Holland, J.*, Sperlea, A.*, Devakanmalai, G. S., Knierer, S., Sangervasi, S.*, Stevenson A., & Özbudak, E. M.(2014). Spatial gradients of protein-level time delays set the pace of the traveling segmentation clock waves.  Development, 141(21), 4158-4167.

Ay, A., Gong, D., & Kahveci, T. (2014). Network-based prediction of cancer under genetic storm.  Cancer Informatics, 13(Suppl 3), 15–31.

Ay, A., & Yildirim, N. (2014). Dynamics matter: differences and similarities between alternatively designed mechanisms.  Molecular BioSystems, 10(7), 1948-1957.

Ay, A., Knierer, S., Sperlea, A.*, Holland, J.*, & Özbudak, E. M. (2013). Short-lived Her proteins drive robust synchronized oscillations in the zebrafish segmentation clock.  Development, 140(15), 3244-3253.

Suleimenov, Y.*, Ay, A., Samee, M. A. H., Dresch, J. M., Sinha, S., & Arnosti, D. N. (2013). Global parameter estimation for thermodynamic models of transcriptional regulation.  Methods, 62(1), 99-108.

Dresch, J. M., Liu, X.*, Arnosti, D. N., & Ay, A. (2010). Thermodynamic modeling of transcription: sensitivity analysis differentiates biological mechanism from mathematical model-induced effects.  BMC Systems Biology, 4(1), 1-11.

Fakhouri, W. D., Ay, A., Sayal, R., Dresch, J., Dayringer, E.*, & Arnosti, D. N. (2010). Deciphering a transcriptional regulatory code: modeling short‐range repression in the  Drosophila embryo.  Molecular Systems Biology, 6(1), 341.

Ay, A., Fakhouri, W. D., Chiu, C., & Arnosti, D. N. (2008). Image processing and analysis for quantifying gene expression from early  Drosophila embryos.  Tissue Engineering Part A, 14(9), 1517-1526.

Ay, A., Gürses, M., & Zheltukhin, K. (2003). Hamiltonian equations in R3.  Journal of Mathematical Physics, 44(12), 5688-5705.

Conference papers:

Ren, Y., Sarkar, A., Ay, A., Dobra, A., & Kahveci, T. (2019) Finding conserved patterns in multilayer networks.  Proceedings of the 10th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 97-102

Chow, K.*, Ay, A., Elhesha, R., & Kahveci, T. (2018) ANCA: Alignment-based Network Construction Algorithm.  Proceedings of the 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 21-26

Ren, Y., Ay, A., Dobra, A. & Kahveci, T. (2018) Characterizing building blocks of resource constrained biological networks.  Proceedings of the 9th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, pp. 581-582

Ren, Y., Ay, A., Gerke, T., & Kahveci T (2018) Searching jointly correlated gene combinations.  Proceedings of the 10th International Conference on Bioinformatics and Computational Biology, BICOB. 

Wang, Q., Ren, Y., Hasan, M. M., Ay, A., & Kahveci, T. (2015) Construction of signaling networks with incomplete RNAi data.  Proceedings of the Bioinformatics and Biomedicine (BIBM) - 2015 IEEE International Conference, pp. 157-162.

Alim, M. A., Ay, A., Hasan, M. M., Thai, M.T., & Kahveci, T. (2015) Multiple reference networks improve accuracy of signaling network construction.  Proceedings of the 6th ACM Conference on Bioinformatics - Computational Biology and Health Informatics, pp. 176-185.

Review papers:

Dresch, J. M., Richards, M.*, & Ay, A. (2013). A primer on thermodynamic-based models for deciphering transcriptional regulatory logic.  BBA Gene Regulatory Mechanisms, 1829(9), 946-953.

Ay, A., & Arnosti, D. N. (2011). Mathematical modeling of gene expression: a guide for the perplexed biologist.  Critical Reviews in Biochemistry and Molecular Biology, 46(2), 

Commentaries:

Arnosti, D. N., & Ay, A. (2012) Boolean modeling of gene regulatory networks: Driesch redux.  PNAS 109(45), 18239-18240. 

Ay, A., & Arnosti, D. N. (2010) Nucleosome positioning: An essential component of the enhancer regulatory code?  Current Biology 20(9), R404-406.

 

  • Picker Interdisciplinary Science Institute, $146000, 2023-2025,  Co-PI on collaborative grant entitled, "New Perspectives on Wild Seal Population Dynamics: Integrating AI, Drones, and e-Genomics", Colgate University, NY
  • Robert H. N. Ho Mind Brain, and Behavior Initiative Discretionary Grant, $3000, 2021, Colgate University, NY
  • Faculty Development Council Grant, $1,500, 2021, Colgate University, NY
  • Robert H. N. Ho Mind, Brain, and Behavior Scholars, $4,200, 2021, Colgate University, NY
  • Best Paper Award, 2018, 10th International Conference on Bioinformatics and Computational Biology (BICOB 2018), Las Vegas, NV
  • Associate Faculty Leave Grant, $20,000, 2017, Colgate University, NY
  • Faculty Research Council Grant, $5,900, 2017, Colgate University, NY
  • Picker Interdisciplinary Science Institute, $153000, 2016-2018, Co-PI on collaborative grant entitled, "An Interdisciplinary Approach to Understanding Ongoing Biological Invasions by Crazy Worms (Amynthas) in North America", Colgate University, NY
  • Picker Interdisciplinary Science Institute, $107000, 2016-2018, Co-PI on collaborative grant entitled, "Interdisciplinary Investigation of the Vertebral Segmentation Clock", Colgate University, NY  
  • Gaurth Hansen Alumnus Award, 2016, Department of Biochemistry and Molecular Biology, Michigan State University, MI
  • Faculty Research Council Grants, 2010-2016, Colgate University, NY
  • Carter Wallace Fellowship, $5000, 2013, Colgate University, NY
  • Faculty Development Council Grant, $1500, 2010, Colgate University, NY
  • Sigma Xi (the scientific research society) Graduate Student Award, 2009, MI
  • Senior Teaching Assistant Award for Excellence in Teaching (Honorable Mention), 2009, Michigan State University, MI
  • Gene Expression in Development and Disease (GEDD) Outstanding Research Award, 2009, Michigan State University, MI
  • GEDD Graduate Student Fellowship, 2008-2009, Michigan State University, MI
  • Quantitative Biology Graduate Student Fellowship, 2007-2008, 2006-2007 Michigan State University, MI