Zobrazeno 1 - 10
of 551
pro vyhledávání: '"phenotype prediction"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-33 (2024)
Abstract Background The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive
Externí odkaz:
https://doaj.org/article/6525ebd742914ad1aa1c5a17ca490b4f
Publikováno v:
Journal of Integrative Bioinformatics, Vol 21, Iss 2, Pp 67-76 (2024)
This study delves into the intricate genetic and clinical aspects of Schizophrenia, a complex mental disorder with uncertain etiology. Deep Learning (DL) holds promise for analyzing large genomic datasets to uncover new risk factors. However, based o
Externí odkaz:
https://doaj.org/article/55f9bfdddeeb4b92bd1b81f78ebb5068
Autor:
Jie Li, Nan Jiang, Hui Zheng, Xiao Zheng, Yi Xu, Yongqing Weng, Feijian Jiang, Chong Wang, Peiliang Chang
Publikováno v:
Annals of Medicine, Vol 56, Iss 1 (2024)
Background Norovirus is the leading cause of sporadic viral gastroenteritis cases and outbreaks. Gut microbiota plays a key role in maintaining immune homeostasis. We aimed to investigate the composition and functional effects of gut microbiota in ch
Externí odkaz:
https://doaj.org/article/157e708e4cf44cdda95fa746b5d8b500
Autor:
Pierfrancesco Novielli, Donato Romano, Stefano Pavan, Pasquale Losciale, Anna Maria Stellacci, Domenico Diacono, Roberto Bellotti, Sabina Tangaro
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
BackgroundAdvances in DNA sequencing revolutionized plant genomics and significantly contributed to the study of genetic diversity. However, predicting phenotypes from genomic data remains a challenge, particularly in the context of plant breeding. D
Externí odkaz:
https://doaj.org/article/6b284edc2512438b8d90f0a9297a8454
Publikováno v:
mSystems, Vol 9, Iss 7 (2024)
ABSTRACT The erythromycin resistance RNA methyltransferase (erm) confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of erm is often induced by the macrolide-mediated
Externí odkaz:
https://doaj.org/article/e554ecb70971406eb5789b1d05ceb22f
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract To explore a robust tool for advancing digital breeding practices through an artificial intelligence-driven phenotype prediction expert system, we undertook a thorough analysis of 11 non-linear regression models. Our investigation specifical
Externí odkaz:
https://doaj.org/article/fe58a596b08f454190423d12b45cd41f
Autor:
Beibei Wang, Yihui Luan
Publikováno v:
Frontiers in Genetics, Vol 15 (2024)
Genotype-to-phenotype mapping is an essential problem in the current genomic era. While qualitative case-control predictions have received significant attention, less emphasis has been placed on predicting quantitative phenotypes. This emerging field
Externí odkaz:
https://doaj.org/article/df050a2eeac44ea797414b0144920fe0
Autor:
Pramod Bharadwaj Chandrashekar, Sayali Alatkar, Jiebiao Wang, Gabriel E. Hoffman, Chenfeng He, Ting Jin, Saniya Khullar, Jaroslav Bendl, John F. Fullard, Panos Roussos, Daifeng Wang
Publikováno v:
Genome Medicine, Vol 15, Iss 1, Pp 1-19 (2023)
Abstract Background Genotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms behind this association remain elusive. With emerging multimodal data for these mechanisms,
Externí odkaz:
https://doaj.org/article/c8c7e6c0ecce42439e257b1b9cc4a68e
Autor:
Dmitry Kolobkov, Satyarth Mishra Sharma, Aleksandr Medvedev, Mikhail Lebedev, Egor Kosaretskiy, Ruslan Vakhitov
Publikováno v:
Frontiers in Big Data, Vol 7 (2024)
Combining training data from multiple sources increases sample size and reduces confounding, leading to more accurate and less biased machine learning models. In healthcare, however, direct pooling of data is often not allowed by data custodians who
Externí odkaz:
https://doaj.org/article/b14112679d3940778ebf1cba9bbd7bc0
Autor:
Yang Fang, Jinshuang Gao, Yaqing Guo, Xiaole Li, Enwu Yuan, Erfeng Yuan, Liying Song, Qianqian Shi, Haiyang Yu, Dehua Zhao, Linlin Zhang
Publikováno v:
Human Genomics, Vol 17, Iss 1, Pp 1-9 (2023)
Abstract Background Phenylketonuria (PKU) is caused by mutations in the phenylalanine hydroxylase (PAH) gene. Our study aimed to predict the phenotype using the allelic genotype. Methods A total of 1291 PKU patients with 623 various variants were use
Externí odkaz:
https://doaj.org/article/a46ca787f2a948c5bc610cd9c3b6589d