Analysis of microbiomes of the ecogenetic series of podzolic soils using an artificial neural network

Переведенное название: Анализ микробиомов экогенетических серий подзолитсых почв с помощью искуственной информационной сети

Ekaterina Ivanova, Elizaveta Pershina, Nadezda Vasilieva, Evgeny Andronov, Evgeny Abakumov

Результат исследований: Научные публикации в периодических изданияхтезисы

Выдержка

The application of molecular-genetic methods is currently one of the necessary steps in the natural microbiomes analysis. The use of these approaches in the study of microbial complexes of soil chronoseries is promising in identifying of taxonomic markers and microbiological drivers of pedogenesis. At the same time, the search for optimal ways of high-throughput sequencing data processing remains relevant today.
Язык оригиналаанглийский
Номер статьиP3
Число страниц1
ЖурналBMC Bioinformatics
Том20
Номер выпускаS17
Ранняя дата в режиме онлайн8 ноя 2019
СостояниеОпубликовано - 2019
Событие3d International Conference «Bioinformatics: from Algorithms to Applications», June 20-June 22, 2019, Saint Petersburg, Russia - Санкт-Петербург, Российская Федерация
Продолжительность: 20 июн 201922 июн 2019
http://biata2019.spbu.ru/wp-content/uploads/2019/06/BiATA2019-BoA.pdf

Отпечаток

Microbiota
soil formation
molecular genetics
neural networks
Sequencing
High Throughput
Artificial Neural Network
Driver
Soil
Molecular Biology
Throughput
Neural networks
Soils
Necessary
Series
soil
methodology
microbiome
ecological genetics

Предметные области Scopus

  • Земледелие и биологические науки (все)

Ключевые слова

  • soils
  • microbiome
  • podzols

Цитировать

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abstract = "The application of molecular-genetic methods is currently one of the necessary steps in the natural microbiomes analysis. The use of these approaches in the study of microbial complexes of soil chronoseries is promising in identifying of taxonomic markers and microbiological drivers of pedogenesis. At the same time, the search for optimal ways of high-throughput sequencing data processing remains relevant today.",
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author = "Ekaterina Ivanova and Elizaveta Pershina and Nadezda Vasilieva and Evgeny Andronov and Evgeny Abakumov",
note = "Ekaterina Ivanova, Elizaveta Pershina, Vasilieva Nadezda, Evgeny Andronov, Evgeny Abakumov Analysis of microbiomes of the ecogenetic series of podzolic soils using an artificial neural network // BIATA2019 congress, 2019, Saint-Petersburg, June 20-22 2019.",
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Analysis of microbiomes of the ecogenetic series of podzolic soils using an artificial neural network. / Ivanova, Ekaterina; Pershina, Elizaveta ; Vasilieva, Nadezda ; Andronov, Evgeny ; Abakumov, Evgeny .

В: BMC Bioinformatics, Том 20, № S17, P3, 2019.

Результат исследований: Научные публикации в периодических изданияхтезисы

TY - JOUR

T1 - Analysis of microbiomes of the ecogenetic series of podzolic soils using an artificial neural network

AU - Ivanova, Ekaterina

AU - Pershina, Elizaveta

AU - Vasilieva, Nadezda

AU - Andronov, Evgeny

AU - Abakumov, Evgeny

N1 - Ekaterina Ivanova, Elizaveta Pershina, Vasilieva Nadezda, Evgeny Andronov, Evgeny Abakumov Analysis of microbiomes of the ecogenetic series of podzolic soils using an artificial neural network // BIATA2019 congress, 2019, Saint-Petersburg, June 20-22 2019.

PY - 2019

Y1 - 2019

N2 - The application of molecular-genetic methods is currently one of the necessary steps in the natural microbiomes analysis. The use of these approaches in the study of microbial complexes of soil chronoseries is promising in identifying of taxonomic markers and microbiological drivers of pedogenesis. At the same time, the search for optimal ways of high-throughput sequencing data processing remains relevant today.

AB - The application of molecular-genetic methods is currently one of the necessary steps in the natural microbiomes analysis. The use of these approaches in the study of microbial complexes of soil chronoseries is promising in identifying of taxonomic markers and microbiological drivers of pedogenesis. At the same time, the search for optimal ways of high-throughput sequencing data processing remains relevant today.

KW - soils

KW - microbiome

KW - podzols

UR - https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6839048/

UR - https://link.springer.com/article/10.1186/s12859-019-3122-9

M3 - Meeting Abstract

VL - 20

JO - BMC Bioinformatics

JF - BMC Bioinformatics

SN - 1471-2105

IS - S17

M1 - P3

ER -