Cargando…

Deep Learning in Population Genetics

Population genetics is transitioning into a data-driven discipline thanks to the availability of large-scale genomic data and the need to study increasingly complex evolutionary scenarios. With likelihood and Bayesian approaches becoming either intractable or computationally unfeasible, machine lear...

Descripción completa

Detalles Bibliográficos
Autores principales:	Korfmann, Kevin, Gaggiotti, Oscar E, Fumagalli, Matteo
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2023
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9897193/ https://www.ncbi.nlm.nih.gov/pubmed/36683406 http://dx.doi.org/10.1093/gbe/evad008

Ejemplares similares

Deciphering signatures of natural selection via deep learning
por: Qin, Xinghu, et al.
Publicado: (2022)

Detecting polygenic selection in marine populations by combining population genomics and quantitative genetics approaches
por: Gagnaire, Pierre-Alexandre, et al.
Publicado: (2016)

KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis
por: Qin, Xinghu, et al.
Publicado: (2022)

Deep Learning for Population Genetic Inference
por: Sheehan, Sara, et al.
Publicado: (2016)

Assessing the Effect of Sequencing Depth and Sample Size in Population Genetics Inferences
por: Fumagalli, Matteo
Publicado: (2013)

High variance in reproductive success generates a false signature of a genetic bottleneck in populations of constant size: a simulation study
por: Hoban, Sean M, et al.
Publicado: (2013)

Changes in selective pressures associated with human population expansion may explain metabolic and immune related pathways enriched for signatures of positive selection
por: Vatsiou, Alexandra I., et al.
Publicado: (2016)

Differentiation measures for conservation genetics
por: Jost, Lou, et al.
Publicado: (2018)

Applications for Deep Learning in Epilepsy Genetic Research
por: Zeibich, Robert, et al.
Publicado: (2023)

Identifying consistent allele frequency differences in studies of stratified populations
por: Wiberg, R. Axel W., et al.
Publicado: (2017)

dnadna: a deep learning framework for population genetics inference
por: Sanchez, Théophile, et al.
Publicado: (2022)

Dispersal and population structure at different spatial scales in the subterranean rodent Ctenomys australis
por: Mora, Matías S, et al.
Publicado: (2010)

Deep Learning of Histopathological Features for the Prediction of Tumour Molecular Genetics
por: Murchan, Pierre, et al.
Publicado: (2021)

ngsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language
por: Mas-Sandoval, Alex, et al.
Publicado: (2023)

The DNA of coral reef biodiversity: predicting and protecting genetic diversity of reef assemblages
por: Selkoe, Kimberly A., et al.
Publicado: (2016)

Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey
por: Hurtado Sánchez, Johanna Andrea, et al.
Publicado: (2022)

Supervised Deep Learning Techniques for Image Description: A Systematic Review
por: López-Sánchez, Marco, et al.
Publicado: (2023)

Beyond the uterine first pass: optimizing programmed frozen embryo transfers. A mini-review
por: Chetkowski, Ryszard J., et al.
Publicado: (2021)

Deep metabolome: Applications of deep learning in metabolomics
por: Pomyen, Yotsawat, et al.
Publicado: (2020)

Deep Learning in Proteomics
por: Wen, Bo, et al.
Publicado: (2020)

Uncovering the Genetic History of the Present-Day Greenlandic Population
por: Moltke, Ida, et al.
Publicado: (2015)

Genome-Wide Identification of Susceptibility Alleles for Viral Infections through a Population Genetics Approach
por: Fumagalli, Matteo, et al.
Publicado: (2010)

Organic fluorescent nanoprobes with NIR‐IIb characteristics for deep learning
por: Wanderi, Kevin, et al.
Publicado: (2022)

Deep learning for computational biology
por: Angermueller, Christof, et al.
Publicado: (2016)

Protein Design with Deep Learning
por: Defresne, Marianne, et al.
Publicado: (2021)

Deep Learning and Antibiotic Resistance
por: Popa, Stefan Lucian, et al.
Publicado: (2022)

Deep Learning Approaches in Histopathology
por: Ahmed, Alhassan Ali, et al.
Publicado: (2022)

Deep Learning in the Medical Domain: Predicting Cardiac Arrest Using Deep Learning
por: Lee, Youngnam, et al.
Publicado: (2018)

Learning for a Robot: Deep Reinforcement Learning, Imitation Learning, Transfer Learning
por: Hua, Jiang, et al.
Publicado: (2021)

Deep learning for prediction of population health costs
por: Drewe-Boss, Philipp, et al.
Publicado: (2022)

Machine Learning and Deep Learning for the Pharmacogenomics of Antidepressant Treatments
por: Lin, Eugene, et al.
Publicado: (2021)

Stable Isotope Ratio Analysis for Authentication of Natural Antioxidant Cannabidiol (CBD) from Cannabis sativa
por: Perini, Matteo, et al.
Publicado: (2023)

Peptides, DNA and MIPs in Gas Sensing. From the Realization of the Sensors to Sample Analysis
por: Gaggiotti, Sara, et al.
Publicado: (2020)

Deep learning enables genetic analysis of the human thoracic aorta
por: Pirruccello, James P., et al.
Publicado: (2022)

Haciendas y recursos territoriales en la modernización agroindustrial azucarera. Una perspectiva desde Morelos, 1880-1913
por: Crespo Gaggiotti, Horacio
Publicado: (2014)

Deep learning and the game of Go
por: Pumperla, Max, et al.
Publicado: (2019)

The Application of Deep Learning on CBCT in Dentistry
por: Fan, Wenjie, et al.
Publicado: (2023)

Automatic Segmentation with Deep Learning in Radiotherapy
por: Isaksson, Lars Johannes, et al.
Publicado: (2023)

Deep Learning and Its Applications in Biomedicine
por: Cao, Chensi, et al.
Publicado: (2018)

Artificial intelligence and deep learning in ophthalmology
por: Ting, Daniel Shu Wei, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_q488b9nc5ofs0b82qdjbe4n3al