Academic Journal
Regression plane concept for analysing continuous cellular processes with machine learning
| Title: | Regression plane concept for analysing continuous cellular processes with machine learning |
|---|---|
| Authors: | Szkalisity A., Piccinini F., Beleon A., Balassa T., Varga I. G., Migh E., Molnar C., Paavolainen L., Timonen S., Banerjee I., Ikonen E., Yamauchi Y., Ando I., Peltonen J., Pietiainen V., Honti V., Horvath P. |
| Contributors: | Szkalisity A., Piccinini F., Beleon A., Balassa T., Varga I.G., Migh E., Molnar C., Paavolainen L., Timonen S., Banerjee I., Ikonen E., Yamauchi Y., Ando I., Peltonen J., Pietiainen V., Honti V., Horvath P. |
| Publication Year: | 2021 |
| Collection: | IRIS Università degli Studi di Bologna (CRIS - Current Research Information System) |
| Subject Terms: | Animal, Carcinoma, Hepatocellular, Cell Cycle, Cell Differentiation, Cell Line, Tumor, Drosophila melanogaster, Human, Membrane Protein, Supervised Machine Learning, Biological Phenomena, Cell Physiological Phenomena, Machine Learning |
| Description: | Biological processes are inherently continuous, and the chance of phenotypic discovery is significantly restricted by discretising them. Using multi-parametric active regression we introduce the Regression Plane (RP), a user-friendly discovery tool enabling class-free phenotypic supervised machine learning, to describe and explore biological data in a continuous manner. First, we compare traditional classification with regression in a simulated experimental setup. Second, we use our framework to identify genes involved in regulating triglyceride levels in human cells. Subsequently, we analyse a time-lapse dataset on mitosis to demonstrate that the proposed methodology is capable of modelling complex processes at infinite resolution. Finally, we show that hemocyte differentiation in Drosophila melanogaster has continuous characteristics. |
| Document Type: | article in journal/newspaper |
| File Description: | ELETTRONICO |
| Language: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/pmid/33953203; info:eu-repo/semantics/altIdentifier/wos/WOS:000656478200010; volume:12; issue:1; firstpage:2532; lastpage:2532; numberofpages:1; journal:NATURE COMMUNICATIONS; https://hdl.handle.net/11585/849968 |
| DOI: | 10.1038/s41467-021-22866-x |
| Availability: | https://hdl.handle.net/11585/849968 https://doi.org/10.1038/s41467-021-22866-x |
| Rights: | info:eu-repo/semantics/openAccess ; license:Licenza per Accesso Aperto. Creative Commons Attribuzione (CCBY) ; license:Licenza per Accesso Aperto. Altra tipologia di licenza compatibile con Open Access ; license uri:iris.PUB15 ; license uri:iris.PUB20 |
| Accession Number: | edsbas.8E8CD3B0 |
| Database: | BASE |
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