Machine Learning as a Tool to Circadian Gene Dynamics Characterization in the Mouse Kidney

הרקע לפרויקט:

Circadian genes regulate biological rhythms that follow a 24-hour cycle, influencing various physiological processes such as sleep, metabolism, and organ function. In the kidney, these genes control the timing of vital functions like electrolyte balance, filtration, and blood pressure regulation. Researching circadian genes in the kidney can improve kidney disease therapy by identifying how disruptions in these rhythms contribute to disease progression and how timing treatments to the body’s natural cycles might enhance their efficacy. Understanding circadian regulation may lead to more personalized and effective therapeutic strategies for kidney disorders.

מטרת הפרויקט:

The aim of this project is to characterize the dynamics of circadian genes in the kidney through the use of machine learning techniques and bioinformatic tools.

תכולת הפרויקט:

Data processing, R programming and algorithm implementation, learning and applying computational methods for analysing time-dependent biological processes, possibility of collaborative work with other labs.

קורסי קדם:

נוירוגנומיקה או ביולוגיה חישובית, מדעי נתונים ביולוגים

דרישות נוספות:

בסיס בשפת תכנות R, מערכת UNIX

מקורות:

1. Bingham, M. A., Neijman, K., Yang, C. R., Aponte, A., Mak, A., Kikuchi, H., Jung, H. J., Poll, B. G., Raghuram, V., Park, E., Chou, C. L., Chen, L., Leipziger, J., Knepper, M. A., & Dona, M. (2023). Circadian gene expression in mouse renal proximal tubule. American journal of physiology. Renal physiology, 324(3), F301–F314. https://doi.org/10.1152/ajprenal.00231.2022
2. Carbonetto, P., Luo, K., Sarkar, A. et al. GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership. Genome Biol 24, 236 (2023). https://doi.org/10.1186/s13059-023-03067-9