CSHL Conference on Probabilistic Modeling in Genomics
- Institution
- COLD SPRING HARBOR LABORATORY, NY
- Principal investigator
- David J. Stewart
- Funding
- $28K
- Duration
- 2025–2030
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Abstract
Probabilistic modeling in genomics involves using statistical and machine-learning methods to analyze genetic data and make inferences about biological processes. Genomic data is inherently noisy and complex, so probabilistic modeling provides a framework for understanding uncertainty and variability in the data. The Cold Spring Harbor Laboratory meetings on Probabilistic Modelling in Genomics are planned for early Spring 2025, 2027 and 2029, and will bring together leading scientists in this growing field, and we strongly encourage researchers from other genome-related disciplines to attend. Probabilistic models in genomics include both more traditional generative modeling frameworks such as Bayesian inference and hidden Markov models (HMMs), and newer machine-learning tools such as deep neural networks, to make predictions and estimate parameters from data. These models can be used to answer a wide range of biological questions, from understanding the genetic basis of disease to reconstructing the evolutionary history of species. The conference is planned around six themes including: 1) Quantitative Genetics and Association Mapping; 2) Machine Learning in Genomics; 3) Population and Statistical Genetics; 4) Demographic Inference; 5) Systems Biology; and 6) Phylogenetics and Phylodynamics. The topics of the meeting are general and nominally span all areas of genomics, but in practice the attendees are dominated by researchers whose focus is human genomics and model organisms. Particular attention will be made to encourage active participation by graduate students, postdoctoral fellows, and new investigators as well as the attendance by leading scientists in the field. We expect this meeting will have a positive impact on the entire genomics workforce. As with the previous four Cold Spring Harbor conferences, it is anticipated that the proposed meetings will provide unique opportunities for the exchange of data, ideas, and latest approaches in this important topic in genome research. The meetings will be international in nature, with an anticipated annual attendance of 250-350 investigators.
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