Novel Machine Learning Methods for Immunosenescence and Aging Research
NIA - National Institute on Aging
About This Grant
PROJECT SUMMARY This proposal aims to develop advanced statistical and computational methods for analyzing immune data to enhance our understanding of the immune system’s role in aging and age-related diseases. Aging is accompanied by significant changes in the immune system, increasing susceptibility to infections, chronic inflammation, and other health challenges. Understanding the heterogeneity of immune profiles and their associations with aging outcomes holds great promise for predicting disease risk and identifying therapeutic targets. Large-scale studies such as the Health and Retirement Study (HRS) provide invaluable data on the elderly population. However, immune data obtained from flow cytometry present unique analytical challenges. These data are compositional, highly skewed, and prone to substantial measurement errors, rendering standard analyses unreliable. Existing methods for supervised and unsupervised analysis of immune data frequently fall short in adjusting for covariates, identifying key immune features, capturing nonlinear relationships, and integrating multiple data sources, resulting in significant gaps in our understanding of immune aging. This proposal addresses these challenges through innovative methodologies. In Aim 1, we will develop a robust nonparametric framework to denoise immune cell frequency data. This framework is free from distributional assumptions and adaptable to diverse data types, enhancing the accuracy of subsequent analyses. In Aim 2, we will create a model-based clustering framework to identify immune subgroups, with a special focus on adjusting for covariates and identifying key drivers of heterogeneity between clusters. In Aim 3, we will develop novel semi-parametric methods to integrate multiple sources of immune biomarkers and associate them with aging outcomes, emphasizing biological interpretability and feature selection. In Aim 4, we will build an open- source software package to ensure the accessibility and wide dissemination of these methods. Motivated by and applied to HRS data, these methods aim to uncover immune signatures in the elderly and clarify their relationship with age-related outcomes. The research will deliver powerful tools for immune data analysis and transformative insights into the interplay between immunity and aging.
Grant Summary
Novel Machine Learning Methods for Immunosenescence and Aging Research is a NIA - National Institute on Aging grant providing up to $298K for university, nonprofit, healthcare org. Applications are due 2031-01-31 (open). Check eligibility and apply with FindGrants.
Focus Areas
Eligibility
How to Apply
Up to $298K
2031-01-31
- 1Confirm your organization is eligible for Novel Machine Learning Methods for Immunosenescence and Aging Research from NIA - National Institute on Aging, checking organization type, location, and any population or project requirements.
- 2Gather the required documents and information, including your organization details, project plan, and budget figures.
- 3Draft your application narrative and budget addressing the funder's priorities and review criteria. FindGrants can draft each section for you to review and edit.
- 4Review every section against the requirements checklist, then export a submission-ready application pack and submit it to NIA - National Institute on Aging before the deadline.
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Novel Machine Learning Methods for Immunosenescence and Aging Research: Frequently Asked Questions
Who is eligible for the Novel Machine Learning Methods for Immunosenescence and Aging Research?
Novel Machine Learning Methods for Immunosenescence and Aging Research is offered by NIA - National Institute on Aging and is generally open to university, nonprofit, healthcare org. It is open to organizations nationwide unless the funder specifies otherwise. Review the specific eligibility terms before applying, since funders set their own requirements around organization type, location, and the population or project being served.
How much funding does the Novel Machine Learning Methods for Immunosenescence and Aging Research provide?
Novel Machine Learning Methods for Immunosenescence and Aging Research provides up to $298K per award from NIA - National Institute on Aging. Actual award sizes depend on the scope of your project, available program funds, and the number of applicants, so build a budget that reflects realistic, allowable costs rather than the maximum figure.
When is the Novel Machine Learning Methods for Immunosenescence and Aging Research deadline?
Applications for Novel Machine Learning Methods for Immunosenescence and Aging Research are due 2031-01-31 (open). Because deadlines can change, verify the date with the funder, NIA - National Institute on Aging, and give yourself enough time to prepare a complete, competitive application before the close date.
How do you apply for the Novel Machine Learning Methods for Immunosenescence and Aging Research?
To apply for Novel Machine Learning Methods for Immunosenescence and Aging Research, confirm your eligibility, gather the required documents, and prepare a narrative and budget that address the funder's priorities. FindGrants guides you step by step and can draft each section, then exports a submission-ready application pack for this grant from NIA - National Institute on Aging.