On Tower and Checkerboard Neural Network Architectures 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%2F20%3A00340463" target="_blank" >RIV/68407700:21230/20:00340463 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1186/s12864-020-06821-6" target="_blank" >https://doi.org/10.1186/s12864-020-06821-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1186/s12864-020-06821-6" target="_blank" >10.1186/s12864-020-06821-6</a>
Alternative languages
Result language
angličtina
Original language name
On Tower and Checkerboard Neural Network Architectures for Gene Expression Inference
Original language description
Background: One possible approach how to economically facilitate gene expression profiling is to use the L1000 platform which measures the expression of ~1,000 landmark genes and uses a computational method to infer the expression of another ~10,000 genes. One such method for the gene expression inference is a D-GEX which employs neural networks. Results: We propose two novel D-GEX architectures that significantly improve the quality of the inference by increasing the capacity of a network without any increase in the number of trained parameters. The architectures partition the network into individual towers. Our best proposed architecture - a checkerboard architecture with a skip connection and five towers - together with minor changes in the training protocol improves the average mean absolute error of the inference from 0.134 to 0.128. Conclusions: Our proposed approach increases the gene expression inference accuracy without increasing the number of weights of the model and thus without increasing the memory footprint of the model that is limiting its usage.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/EF16_019%2F0000765" target="_blank" >EF16_019/0000765: Research Center for Informatics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
BMC Genomics
ISSN
1471-2164
e-ISSN
1471-2164
Volume of the periodical
21
Issue of the periodical within the volume
5
Country of publishing house
GB - UNITED KINGDOM
Number of pages
11
Pages from-to
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UT code for WoS article
000601211700003
EID of the result in the Scopus database
2-s2.0-85097603076