Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 148 tok/s
Gemini 2.5 Pro 44 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 30 tok/s Pro
GPT-4o 86 tok/s Pro
Kimi K2 197 tok/s Pro
GPT OSS 120B 458 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

mvlearnR and Shiny App for multiview learning (2311.16181v1)

Published 25 Nov 2023 in q-bio.GN, cs.LG, stat.AP, and stat.ME

Abstract: The package mvlearnR and accompanying Shiny App is intended for integrating data from multiple sources or views or modalities (e.g. genomics, proteomics, clinical and demographic data). Most existing software packages for multiview learning are decentralized and offer limited capabilities, making it difficult for users to perform comprehensive integrative analysis. The new package wraps statistical and machine learning methods and graphical tools, providing a convenient and easy data integration workflow. For users with limited programming language, we provide a Shiny Application to facilitate data integration anywhere and on any device. The methods have potential to offer deeper insights into complex disease mechanisms. Availability and Implementation: mvlearnR is available from the following GitHub repository: https://github.com/lasandrall/mvlearnR. The web application is hosted on shinyapps.io and available at: https://multi-viewlearn.shinyapps.io/MultiView_Modeling/

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.