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On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F21%3A00346215" target="_blank" >RIV/68407700:21230/21:00346215 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1371/journal.pone.0243915" target="_blank" >https://doi.org/10.1371/journal.pone.0243915</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1371/journal.pone.0243915" target="_blank" >10.1371/journal.pone.0243915</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On Transformative Adaptive Activation Functions in Neural Networks for Gene Expression Inference

  • Original language description

    Gene expression profiling was made more cost-effective by the NIH LINCS program that profiles only ~1, 000 selected landmark genes and uses them to reconstruct the whole profile. The D–GEX method employs neural networks to infer the entire profile. However, the original D–GEX can be significantly improved. We propose a novel transformative adaptive activation function that improves the gene expression inference even further and which generalizes several existing adaptive activation functions. Our improved neural network achieves an average mean absolute error of 0.1340, which is a significant improvement over our reimplementation of the original D–GEX, which achieves an average mean absolute error of 0.1637. The proposed transformative adaptive function enables a significantly more accurate reconstruction of the full gene expression profiles with only a small increase in the complexity of the model and its training procedure compared to other methods.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    PLoS ONE

  • ISSN

    1932-6203

  • e-ISSN

    1932-6203

  • Volume of the periodical

    16

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    27

  • Pages from-to

    1-27

  • UT code for WoS article

    000609988100038

  • EID of the result in the Scopus database

    2-s2.0-85099882182