Polygenic prediction and gene regulation networks by Juan F. Poyatos

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Histological Analysis of Oral Tissue Grafting: A Focus on Donor Site Selection by Piero Antonio Zecca, Alice Ronchetti, Doris Cangelosi, Marcella Reguzzoni, Davide Farronato

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Predicting MDS-UPDRS-III score changes using mobile device biomarkers by Semkiv Khrystyna, Schreiner Simon J., Blaser Gian E., Baumann Christian R., Karlen Walter

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Dynamic star allele definitions in Pharmacogenomics: impact on diplotype calls, Phenotype predictions and statin therapy recommendations by Sven van der Maas, Sven van der Maas, Sven van der Maas, Simon Denil, Brigitte Maes, Brigitte Maes, Gökhan Ertaylan, Pieter-Jan Volders, Pieter-Jan Volders, Pieter-Jan Volders

“…Diplotypes of the samples were updated based on predefined criteria. Phenotype predictions and therapeutic recommendations were inferred using the PyPGx core API, with CPIC guidelines applied for statin-phenotype combinations.ResultsWe reevaluated 1400 diplotypes across 20 pharmacogenes in 70 samples from the GeT-RM dataset using three star allele callers: Aldy, PyPGx, and StellarPGx. …”
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Genotype-Driven Phenotype Prediction in Onion Breeding: Machine Learning Models for Enhanced Bulb Weight Selection by Junhwa Choi, Sunghyun Cho, Subin Choi, Myunghee Jung, Yu-jin Lim, Eunchae Lee, Jaewon Lim, Han Yong Park, Younhee Shin

“…We identified 51,499 high-quality variants and employed these data to construct a genomic estimated breeding value (GEBV) model and apply machine learning methods for bulb weight prediction. Validation with 260 new individuals revealed that the machine learning model achieved an accuracy of 83.2% and required only thirty-nine SNPs. …”
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Analysis of Bacterial Communities and Prediction of Functions and Phenotypes in the Preparation of High Temperature Daqu Using Different Methods by Huijun ZHAO, Yurong WANG, Qiangchuan HOU, Haibo ZHANG, Longxin TIAN, Mingbo YE, Zhuang GUO

“…Through phenotype prediction, it was found that the content of gram-positive bacteria in the mechanical starter-making samples was more abundant (P<0.05), while the ability of oxidative stress tolerance in the artificial starter-making samples was stronger (P<0.05). …”
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Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. by Deborah Kunkel, Peter Sørensen, Vijay Shankar, Fabio Morgante

“…Polygenic prediction of complex trait phenotypes has become important in human genetics, especially in the context of precision medicine. …”
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Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets by Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann

“…Abstract Predicting prokaryotic phenotypes—observable traits that govern functionality, adaptability, and interactions—holds significant potential for fields such as biotechnology, environmental sciences, and evolutionary biology. …”
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Biological age model using explainable automated CT-based cardiometabolic biomarkers for phenotypic prediction of longevity by Perry J. Pickhardt, Michael W. Kattan, Matthew H. Lee, B. Dustin Pooler, Ayis Pyrros, Daniel Liu, Ryan Zea, Ronald M. Summers, John W. Garrett

“…The final weighted CT biomarker selection was based on the index of prediction accuracy. The CT model significantly outperforms standard demographic data for predicting longevity (IPA = 29.2 vs. 21.7; 10-year AUC = 0.880 vs. 0.779; p < 0.001). …”
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Evaluating the potential of phenotypic age to enhance cardiovascular risk prediction over chronological age in the UK Biobank by Kristine J. S. Kwan, Shi-Shuai Xie, Hai-Lei Li, Xue-Guang Lin, Yi-Jie Lu, Bo Chen, Kai-Xin Ge, Shu-Ya Tang, Hui Zhang, Shuai Jiang, Jing-Dong Tang

“…Abstract Phenotypic age acceleration (PhenoAgeAccel) is a novel biological indicator estimates an individual’s mortality risk. …”
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Integrated phenotypic analysis, predictive modeling, and identification of novel trait-associated loci in a diverse Theobroma cacao collection by Insuck Baek, Minhyeok Cha, Seunghyun Lim, Brian M. Irish, Sookyung Oh, Jishnu Bhatt, Rakesh K. Upadhyay, Moon S. Kim, Lyndel W. Meinhardt, Sunchung Park, Ezekiel Ahn

“…We also developed machine learning (ML) models for yield prediction and identified yield-associated SNP markers. …”
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Modelling hepatocellular carcinoma microenvironment phenotype to evaluate drug efficacy by Sara Cherradi, Salomé Roux, Marie Dupuy, Séverine Tabone-Eglinger, Edouard Tuaillon, Marianne Ziol, Eric Assenat, Hong Tuan Duong

“…Treating HCC is challenging because of the poor drug effectiveness and the lack of tools to predict patient responses. To resolve these issues, we established a patient-centric spheroid model using HepG2, TWNT-1, and THP-1 co-culture, that mimics HCC phenotype. …”
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The Prediction of Type 1 Diabetes in discordant and concordant families: 16 years of follow-up. Focus on the future by Elena Vital'evna Titovich, Tamara Leonidovna Kuraeva, Olga Nikolaevna Ivanova, Svetlana Mikhailovna Stepanova, Valentina Alexandrovna Peterkova, Ivan Ivanovich Dedov

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Use of Phenomics in the Selection of UAV-Based Vegetation Indices and Prediction of Agronomic Traits in Soybean Subjected to Flooding by Charleston dos Santos Lima, Darci Francisco Uhry Junior, Ivan Ricardo Carvalho, Christian Bredemeier

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Predicting Autism Spectrum Disorder Based on Parents’ Traits by Kaitlin Cole, Angie Kamel, Christopher "Gabby" Vento, Gwen Hoffman, Elissar Andari

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Behavioral fingerprints predict insecticide and anthelmintic mode of action by Adam McDermott‐Rouse, Eleni Minga, Ida Barlow, Luigi Feriani, Philippa H Harlow, Anthony J Flemming, André E X Brown

“…Here, we use high‐throughput imaging and quantitative phenotyping to measure Caenorhabditiselegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. …”
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Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction by Ruidong Xiang, Chief Ben-Eghan, Yang Liu, David Roberts, Scott Ritchie, Samuel A. Lambert, Yu Xu, Fumihiko Takeuchi, Michael Inouye

“…Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. …”
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High-throughput 3D phenotyping in northern quahogs Mercenaria mercenaria for dimensional trait measurement and weight prediction by Kai Shen, Xu Wang, Kai Gao, Jayme Yee, Paul McDonald, Huiping Yang

“…Moreover, this method can be extended to accurate and fast phenotyping of other bivalve species, representing a substantial advancement in broodstock breeding technologies.…”
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Construction and Optimization of Integrated Yield Prediction Model Based on Phenotypic Characteristics of Rice Grown in Small–Scale Plantations by Jihong Sun, Peng Tian, Zhaowen Li, Xinrui Wang, Haokai Zhang, Jiangquan Chen, Ye Qian

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A review of enhanced biosignature immunotherapy tools for predicting lung cancer immune phenotypes using deep learning by A. Sheryl Oliver, Md Shohel Sayeed, Siti Fatimah Abdul Razak

“…This review explores the application of advanced deep learning (DL) techniques in enhancing biosignature immunotherapy tools for the prediction of immune phenotypes in lung cancer patients. …”
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