Supervised Machine Learning for Population Genetics: A New Paradigm

Schrider, Daniel R., Kern, Andrew D.·2018·Trends in Genetics

Cited by (459)

Items 401–459 of 459

  1. Genetics and Population Analysis
    Prachi Balyan, Nismabi A Nisamudheen, Zainab Jan, Dinesh Velayutham, Manoj K Balyan, Puthen Veettil Jithesh · 2025 · Elsevier eBooks
  2. Perspectives of Population Genetics in the Genetic Improvement and Biodiversity Conservation of Fish Species
    Marcos Edgar Herkenhoff · 2025 · Genetics.
  3. ConfuseNN: Interpreting convolutional neural network inferences in population genomics with data shuffling
    Linh N. Tran, David Castellano, Ryan N. Gutenkunst · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  4. Neutral Evolution, Population Genetic Tests of
    Christian D. Huber, Kirk E. Lohmueller · 2025 · Elsevier eBooks
  5. Historical Fragmentation in Atlantic Forest Explains the Diversification of a Clade of Mountaintop Bromeligenous Frogs (Leptodactylidae: Crossodactylodes)
    Marcus Thadeu T. Santos, Marcelo Gehara, Caroline Batistim Oswald, Rodrigo Lopes Ferreira, Fabrício Rodrigues dos Santos, Paulo Christiano de Anchieta Garcia, Kelly Raquel Zamudio, Célio F. B. Haddad, Rafael Félix de Magalhães · 2025 · Zoologica Scripta
  6. Intricate interactions between fine-scale genetic structure, lifestyle, and dietary habits in the Japanese population
    Yichi Chen, Kotoe Katayama, Sachiko Ishida, Seiya Imoto · 2025 · Communications Biology
  7. Opportunities of Big Data in Agricultural Water Management
    Khadija Shabbir, Mazhar Ali, Muhammad Mubeen, Qurat-ul-ain Maken, Saeed Ahmad Qaisrani, Fahd Rasul, Ashfaq Ahmad · 2025 · Springer eBooks
  8. GHIST 2024: The 1st Genomic History Inference Strategies Tournament
    Travis J. Struck, Andrew H. Vaughn, Austin Daigle, Dylan D. Ray, Ekaterina Noskova, Jaison Jeevan Sequeira, Svetlana Antonets, Elizaveta Alekseevskaya, Elizaveta Grigoreva, Evgenii Raines et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  9. Inference of germinal center evolutionary dynamics via simulation-based deep learning
    Duncan Ralph, Athanasios G Bakis, Jared Galloway, Ashni A Vora, Tatsuya Araki, Gabriel D. Victora, Yun S. Song, William S. DeWitt, Frederick A. Matsen IV · 2026 · eLife
  10. Systematic selection of best performing mathematical models for in vitro gas production using machine learning across diverse feeds
    Hamed Ahmadi, Natascha Titze, Katharina Judith Wild, M. Rodehutscord · 2025 · Scientific Reports
  11. Inference of germinal center evolutionary dynamics via simulation-based deep learning
    Duncan Ralph, Athanasios G Bakis, Jared Galloway, Ashni A Vora, Tatsuya Araki, Gabriel D. Victora, Yun S. Song, William S. DeWitt, Frederick A. Matsen IV · 2025 · eLife
  12. Inference of germinal center evolutionary dynamics via simulation-based deep learning
    Duncan Ralph, Athanasios G Bakis, Jared Galloway, Ashni A Vora, Tatsuya Araki, Gabriel D. Victora, Yun S. Song, William S. DeWitt, Frederick A. Matsen IV · 2025 · eLife
  13. Simulations of Life History Variation for Demographic Inference From Population Genomic Data
    Rilquer Mascarenhas, Michael J. Hickerson, Ana Carolina Carnaval · 2025 · Molecular Ecology
  14. Additional file 6 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  15. Additional file 2 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  16. Additional file 4 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, Comas, David · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  17. Additional file 2 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, David Comas · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  18. Additional file 3 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, Comas, David · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  19. Additional file 2 of Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs
    Jamal Momeni, Melanie Parejo, Rasmus O. Nielsen, Langa, Jorge, Iratxe Montes, Laetitia Papoutsis, Leila Farajzadeh, Bendixen, Christian, Eliza Căuia, Charrière, Jean-Daniel et al. · 2021 · Figshare
  20. Additional file 5 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  21. Additional file 7 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  22. Additional file 1 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  23. Additional file 4 of Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs
    Jamal Momeni, Melanie Parejo, Rasmus O. Nielsen, Langa, Jorge, Iratxe Montes, Laetitia Papoutsis, Leila Farajzadeh, Bendixen, Christian, Eliza Căuia, Charrière, Jean-Daniel et al. · 2021 · Figshare
  24. Additional file 5 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, Comas, David · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  25. Additional file 6 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, Comas, David · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  26. Additional file 4 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  27. Additional file 15 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  28. Additional file 1 of Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival
    Kosyakovsky, Leah B., Somerset, Emily, Angela J. Rogers, Sklar, Michael, Jared R. Mayers, Toma, Augustin, Yishay Szekely, Sabri Soussi, Bo Wang, Fan, Chun-Po S. et al. · 2022 · Figshare
  29. Additional file 3 of Authoritative subspecies diagnosis tool for European honey bees based on ancestry informative SNPs
    Jamal Momeni, Melanie Parejo, Rasmus O. Nielsen, Langa, Jorge, Iratxe Montes, Laetitia Papoutsis, Leila Farajzadeh, Bendixen, Christian, Eliza Căuia, Charrière, Jean-Daniel et al. · 2021 · Figshare
  30. Additional file 3 of Machine-learning algorithms based on personalized pathways for a novel predictive model for the diagnosis of hepatocellular carcinoma
    Cheng, Binglin, Peitao Zhou, Chen, Yuhan · 2022 · Figshare
  31. Additional file 1 of Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations
    Jose M Serradell, Jose Miguel Lorenzo-Salazar, Flores, Carlos, Óscar Lao, Comas, David · 2024 · DIGITAL.CSIC (Spanish National Research Council (CSIC))
  32. BPformer: An Interpretable Deep Learning Framework for Livestock Breed Proportion Analysis
    Jinpeng Wang, Shuo Sun, Yaran Zhang, Zhihua Ju, Qiang Jiang, Xiuge Wang, Yao Xiao, Lingxi Chen, Jinming Huang · 2025 · Research Square
  33. Learning to explore tree neighbourhoods for phylogenetic inference
    Federico Julian Camerota Verdù, Andrea Gasparin, Luca Bortolussi, Lorenzo Castelli · 2026 · Briefings in Bioinformatics
  34. Genomic and Molecular Bases of Pollination Syndrome Evolution
    Tianyu Cui, Yaowu Yuan · 2026 · Annual Review of Plant Biology
  35. Discriminating models of trait evolution
    Jenniffer Roa Lozano, Surbhit Jangra, Michael DeGiorgio, Raquel Assis, Rich Adams · 2026 · Evolution
  36. ARGformer: learning on ancestral recombination graphs with transformers
    David Bonet, Cole Shanks, Marçal Comajoan Cara, Jordi Abante, Alexander G. Ioannidis · 2026 · Bioinformatics
  37. Summary statistics and approximate bayesian computation are comparable to convolutional neural networks for inferring times to fixation
    Miles D. Roberts, Emily B. Josephs · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  38. Inference of germinal center evolutionary dynamics via simulation-based deep learning
    Duncan Ralph, Athanasios G Bakis, Jared Galloway, Ashni A. Vora, Tatsuya Araki, Gabriel D. Victora, Yun S Song, William S. DeWitt, Frederick A. Matsen IV · 2026 · eLife
  39. Plasticity and genetic adaptation as contributors to the evolutionary history of cultivated maize and its wild relatives
    Anne Lorant · 2018 · theses.fr (ABES)
  40. Forêts aléatoires pour données longitudinales de grande dimension
    Louis Capitaine · 2020
  41. Deep learning from phylogenies
    Jakub Voznica · 2021 · theses.fr (ABES)
  42. Deep learning for population genetics : inferring demography and targets of natural selection using convolutional neural networks
    Guillaume Lan-Fong · 2024 · theses.fr (ABES)
  43. Role and Application of Machine Learning Techniques in Early Diagnosis and Management of Autoimmune Diseases
    Akshay Chadha, Naman Garg · 2026 · Springer eBooks
  44. Harnessing Deep Learning in Searching Wild Relatives of Domestic Animals
    Zheng‐Fei Cai, Bei Liu, Ting-Ting Yin, Cheng Ma, Zi‐Teng Han, Li‐Hong Gu, Chao Zhang, Fei Wu, Li‐Sheng Liu, Xian Shi et al. · 2026 · Molecular Ecology Resources
  45. Genetic basis of temporal variation in phenology in a woody perennial plant
    Yang Liu · 2026 · npj Systems Biology and Applications
  46. Beyond Classical Limits: How Quantum SVMs and Feature Maps Revolutionize Machine Learning
    Asif Mohammed Saad, Kh Ehsanur Rahman, Md. Farhan Shahriyar, Yuldasheva Gulora, Ha Meem Hossain · 2026 · Lecture notes in networks and systems
  47. On the use of generative models for demographic inference in malaria vectors from genomic data
    Amelia Adibe Eneli, Pui Chung Siu, Manolo F. Perez, Austin Burt, Matteo Fumagalli, Sara Mathieson · 2026 · G3 Genes Genomes Genetics
  48. A Rarefaction Approach to Identify Local Introgression in a Three Population Tree
    T. C. Smith, Zachary A. Szpiech · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  49. A machine learning integrated multi-omics framework for risk prediction and target discovery in insomnia aggravated sepsis induced acute lung injury
    Jinquan Zhang, Yuwei Zhang, Z.H. Liu, Xiaona Chen, Zhengzheng Yan, Zhixia Chen, Qi Li · 2026 · Frontiers in Immunology
  50. Artificial Intelligence in the biological sciences
    Luis Carlos Martínez, Angelica Plata‐Rueda · 2026 · Acta Biológica Colombiana
  51. Negative frequency-dependent selection: a positive outlook with deep learning
    Cindy G. Santander, André Luiz Campelo dos Santos, Sandipan Paul Arnab, Matteo Fumagalli, Michael DeGiorgio · 2026 · Philosophical Transactions of the Royal Society B Biological Sciences
  52. Detecting introgression from phylogenetic invariant site patterns using machine learning
    Patrick McKenzie, Deren A. R. Eaton · 2026 · Applications in Plant Sciences
  53. Methods for Detecting Adaptive Molecular Evolution
    Pauline L. Kamath · 2026 · Oxford University Press eBooks
  54. Genomic Selection for Milk Yield and Milk Composition Traits in Dairy Goats Using Machine Learning and Prior-Information Models
    Jianqing Zhao, Wei L Wang, Jiayidaer Kamalibieke, Yuanpan Mu, Jun Luo · 2026 · Animals
  55. From Andes to the dry diagonal: phylogenomics and trait evolution elucidate the radiation of cacti in South American drylands
    Monique Romeiro‐Brito, Flávia M. Lanna, Milena C. Telhe, Bryan C. Carstens, Luciano Antônio Digiampietri, DANIELA CRISTINA ZAPPI, Nigel P. Taylor, Fernando F Franco, Evandro Marsola Moraes · 2026 · Molecular Phylogenetics and Evolution
  56. AI-driven tri-typing in agriculture: Current advances, future frontiers
    Shabbir Hussain, Ishrat Naureen, Madiha Habib, Faisal Saeed Awan, Hasham Feroz Ghuman, Alam Sher, Muhammad Waheed Riaz, Hafiz Muhammad Usman, Saddam Hussain, Fanmei Kong et al. · 2026 · Molecular Breeding
  57. This must be the place: deep learning local adaptation
    Jordan T. Rodriguez, Richard Cronn, Silas B. Tittes, Andrew D. Kern · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  58. Trends in Plant Breeding and Genetics
    Andrés J. Cortés · 2026 · International Journal of Molecular Sciences
  59. From Mechanistic Models to AI Synergy: A Roadmap for Predictive and Personalized Biology
    Letong Huang, Hongqin Sun, Yi Huang, Qingyi Gu, Hailong Zhang, Dingqin He, Wenyi Zhang, Siyu Chen, Delin Xu, Juanjuan Zhao · 2026 · Biology