Ансамблевые методы в биоинформатике: опыт их применения в геномике и QSAR моделировании

  • № 3(9) 2017

Страницы: 

87

 – 

94

Язык: русский

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Аннотация

Сегодня исследования в вычислительной биологии широко используют методы ансамбля из-за их уникальных преимуществ в работе с выборками малых размеров, высокой размерности признаков, и сложных структур данных. Эта статья имеет две цели. Первая,- дать обзор наиболее широко используемых методов обучения ансамбля и их применения в различных задачах биоинформатики, — экспрессии генов, протеомики на основе масс-спектрометрии , идентификации взаимодействия генов и прогнозирования регуляторных элементов из последовательностей ДНК и белков, QSAR моделировании. Вторая цель,- обобщить тенденции будущего развития методов ансамбля в области биоинформатики. Обсуждаются перспективные направления, такие как ансамбль опорных векторов, мета-ансамбль, и ансамбль для отбора признаков.

Ensemble learning is an intensively studies technique in machine learning and pattern recognition. Recent work in computational biology has seen an increasing use of ensemble learning methods due to their unique advantages in dealing with small sample size, high-dimensionality, and complexity data structures. The aim of this article is two-fold. First, it is to provide a review of the most widely used ensemble learning methods and their application in various bioinformatics problems, including the main topics of gene expression, mass spectrometry-based proteomics, gene-gene interaction identification from genome-wide association studies, prediction of regulatory elements from DNA and protein sequences and QSAR modelling. Second aim is to identify and summarize future trends of ensemble methods in bioinformatics. Promising directions such as ensemble of support vector machine, meta-ensemble, and ensemble based feature selection are discussed.

Бугунги кунда ҳисоблаш биологияси тадқиқодларида кичик ўлчамли танланмалар, юқори ўлчамли белгилар ва маълумотларнинг мураккаб структуралари билан ишлашда яққол устунлиги туфайли ансамблли методлардан қўлланилади. Мақолада асосий икки мақсад кўзланган. Биринчиси ген экспрессияси, масс-спектрометрия асосида протеомикалар, генлар ўзаро таъсир идентификация ДНК ва оқсил кетма кетликларидан регулятор элементларини башоратлаш QSAR моделлаштириш каби биоинформатиканинг турли масалаларида кенг қўлланилаётган ансамблли ўрганиш методларини тахлилини келтириш. Иккинчи биоинформатика соҳасида келажакда ансамблли методларни ривожланиш йўналишларини умумлаштириш. Таянч векторлар ансамбли, мета ансамбл ва белгиларни танлаш учун ансамбл каби перспектив йўналишлар муҳокама қилинади.

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Список всех публикаций, цитирующих данную статью