Integrating Significant SNPs Identified by GWAS for Genomic Prediction of the Number of Ribs and Carcass Length in Suhuai Pigs by Kaiyue Liu, Yanzhen Yin, Binbin Wang, Chenxi Liu, Wuduo Zhou, Peipei Niu, Ruihua Huang, Pinghua Li, Qingbo Zhao

“…The traits are usually measured after slaughter. To improve the prediction performance of genomic selection (GS) for NRs and CL, one strategy is to integrate the significant loci identified from whole-genome sequencing (WGS) data by genome-wide association study (GWAS) into the genomic prediction (GP) model. …”
Get full text

Multimodal data integration for biologically-relevant artificial intelligence to guide adjuvant chemotherapy in stage II colorectal cancerResearch in context by Chenyi Xie, Ziyu Ning, Ting Guo, Lisha Yao, Xiaobo Chen, Wanghong Huang, Suyun Li, Jiahui Chen, Ke Zhao, Xiuwu Bian, Zhenhui Li, Yanqi Huang, Changhong Liang, Qingling Zhang, Zaiyi Liu

“…Further experiments confirmed that changes in vessel morphology led to alterations in predictive imaging features. Interpretation: The developed explainable AI-powered analyser effectively identified patients with stage II CRC with improved overall survival after receiving adjuvant chemotherapy, thereby contributing to the advancement of precision oncology. …”
Get full text

SCONe: a community-acquired retinal image repository enabling ocular, cardiovascular and neurodegenerative disease prediction by Tom Macgillivray, Andrew J Tatham, Niall Strang, Baljean Dhillon, Robert Wallace, Heather Anderson, Miguel O Bernabeu, Claire Tochel, Alice McTrusty, Emma Pead, Fiona Buckmaster, Jonathan Penny, Malihe Javidi, Ana Paula Rubio, Jamie B R Kidd, Ruairidh MacLeod

“…The linked data allow the application of condition labels or phenotypes at specific points in time, facilitating research into retinal manifestations of vascular and neural diseases. …”
Get full text

Predicting IDH and 1p/19q molecular status of gliomas with multi-b values DWI by Shanshan Zhao, Peipei Wang, Eryuan Gao, Mengzhu Wang, Guang Yang, Shouhui Niu, Mengjiao Pan, Kai Zhao, Jingliang Cheng, Xiaoyue Ma

“…However, the application of CTRW model in prediction of IDH and 1p/19q molecular phenotypes in adult diffuse gliomas remains underreported. …”
Get full text

Leveraging Automated Machine Learning for Environmental Data‐Driven Genetic Analysis and Genomic Prediction in Maize Hybrids by Kunhui He, Tingxi Yu, Shang Gao, Shoukun Chen, Liang Li, Xuecai Zhang, Changling Huang, Yunbi Xu, Jiankang Wang, Boddupalli M. Prasanna, Sarah Hearne, Xinhai Li, Huihui Li

“…Abstract Genotype, environment, and genotype‐by‐environment (G×E) interactions play a critical role in shaping crop phenotypes. Here, a large‐scale, multi‐environment hybrid maize dataset is used to construct and validate an automated machine learning framework that integrates environmental and genomic data for improved accuracy and efficiency in genetic analyses and genomic predictions. …”
Get full text

Early prediction of preeclampsia from clinical, multi-omics and laboratory data using random forest model by Qiang Zhao, Jia Li, Zhuo Diao, Xiao Zhang, Suihua Feng, Guixue Hou, Wenqiu Xu, Zhiguang Zhao, Zhixu Qiu, Wenzhi Yang, Si Zhou, Peirun Tian, Qun Zhang, Weiping Chen, Huahua Li, Gefei Xiao, Jie Qin, Liqing Hu, Zhongzhe Li, Liang Lin, Shunyao Wang, Ruyun Gao, Wuyan Huang, Xiaohong Ruan, Sufen Zhang, Jianguo Zhang, Lijian Zhao, Rui Zhang

“…Abstract Background Predicting preeclampsia (PE) within the first 16 weeks of gestation is difficult due to various risk factors, poorly understood causes and likely multiple pathogenic phenotypes of preeclampsia.  …”
Get full text

Sputum bacterial microbiota signature as a surrogate for predicting disease progression of nontuberculous mycobacterial lung disease by Hung-Ling Huang, Chieh-Hua Lin, Meng-Rui Lee, Wei-Chang Huang, Chau-Chyun Sheu, Meng-Hsuan Cheng, Po-Liang Lu, Cheng-Hsieh Huang, Yao-Tsung Yeh, Jinn-Moon Yang, Inn-Wen Chong, Yu-Chieh Liao, Jann-Yuan Wang

“…Objectives: Predicting progression of nontuberculous mycobacterial lung disease (NTM-LD) remains challenging. …”
Get full text

GRK5 as a Novel Therapeutic Target for Immune Evasion in Testicular Cancer: Insights from Multi-Omics Analysis and Immunotherapeutic Validation by Congcong Xu, Qifeng Zhong, Nengfeng Yu, Xuqiang Zhang, Kefan Yang, Hao Liu, Ming Cai, Yichun Zheng

Get full text

The relationship between serum uric acid level and concentration of proangiogenic endothelial progenitor cells in chronic heart failure patients by A. A. Kremzer

“…the objective of this study: to establish predictive relationship between the content of uric acid in the blood and the level of circulating endothelial progenitor cells in patients with CHF of ischemic origin. …”
Get full text

Predicting Postoperative Re-Tear of Arthroscopic Rotator Cuff Repair Using Artificial Intelligence on Imbalanced Data by Zhibin Zhang, Zhewei Zhang, Zhaoxiang Peng, Yihong Dong

“…Retears after rotator cuff surgery are a common complication. Accurate prediction of retear is essential to minimise the risk of retear. …”
Get full text

Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility. by Irene V van Blokland, Pauline Lanting, Anil P S Ori, Judith M Vonk, Robert C A Warmerdam, Johanna C Herkert, Floranne Boulogne, Annique Claringbould, Esteban A Lopera-Maya, Meike Bartels, Jouke-Jan Hottenga, Andrea Ganna, Juha Karjalainen, Lifelines COVID-19 cohort study, COVID-19 Host Genetics Initiative, Caroline Hayward, Chloe Fawns-Ritchie, Archie Campbell, David Porteous, Elizabeth T Cirulli, Kelly M Schiabor Barrett, Stephen Riffle, Alexandre Bolze, Simon White, Francisco Tanudjaja, Xueqing Wang, Jimmy M Ramirez, Yan Wei Lim, James T Lu, Nicole L Washington, Eco J C de Geus, Patrick Deelen, H Marike Boezen, Lude H Franke

“…Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. …”
Get full text

Identification and virulence factors prediction of Didymella segeticola causing leaf spot disease in Asarum heterotropoides in China by Kun Liu, Wensong Sun, Xiaoli Li, Baoyu Shen, Tianjing Zhang, Chunlei Yu

Get full text

Construction and validation of a necroptosis-related lncRNA signature for predicting the prognosis of gastrointestinal cancer patients by Weicheng Huang, Weicheng Huang, Weicheng Huang, Weicheng Huang, Yuchen Liu, Yuchen Liu, Yuchen Liu, Yuchen Liu, Ruyi Liu, Ruyi Liu, Ruyi Liu, Ruyi Liu, Chi Feng, Chi Feng, Chi Feng, Chi Feng, Jiehua Wu, Jiehua Wu, Jiehua Wu, Jiehua Wu, Xing Sun, Xing Sun, Xing Sun, Xing Sun, Pengfei Zhu, Pengfei Zhu, Pengfei Zhu, Pengfei Zhu, Pengxiang Chen, Pengxiang Chen, Pengxiang Chen, Pengxiang Chen, Yufeng Cheng, Yufeng Cheng, Yufeng Cheng, Yufeng Cheng

“…Furthermore, in vitro phenotypic assays demonstrated that the lncRNAs included in the Necro-lnc score play critical roles in the progression and metastasis of GI cancer.ConclusionThis study developed the promising Necro-lnc score, which demonstrates potential for predicting prognosis and distinguishing between cold and hot tumors, thereby improving personalized treatment strategies for patients with GI cancer.…”
Get full text

Longitudinal accumulation of glial activation measured by TSPO-PET predicts later brain atrophy in multiple sclerosis by Nylund Marjo, Lehto Jussi, Matilainen Markus, Rajander Johan, Wahlroos Saara, Sucksdorff Marcus, Kuhlmann Tanja, Airas Laura

Get full text

Variance reduction and measurement errors in estimating lactation milk yields using best prediction: An analytical review by Xiao-Lin Wu, Paul M. VanRaden, John Cole, H. Duane Norman

“…Best prediction (BP) has been used in the United States to estimate unobserved daily and lactation yields from known test-day yields since 1999. …”
Get full text

Tumor microenvironment assessment-based signatures for predicting response to immunotherapy in non-small cell lung cancer by Jiani Wu, Yuanyuan Wang, Zhenhua Huang, Jingjing Wu, Huiying Sun, Rui Zhou, Wenjun Qiu, Zilan Ye, Yiran Fang, Xiatong Huang, Jianhua Wu, Jianping Bin, Yulin Liao, Min Shi, Jiguang Wang, Wangjun Liao, Dongqiang Zeng

“…High IKCscore was characterized by inflammatory tumor microenvironment phenotype and higher T cell receptor diversity. The IKCscore exhibits promise as a bioindicator that can predict the efficacy of both immunotherapy and immunotherapy-based combination therapies, while providing guidance for personalized therapeutic strategies for advanced NSCLC patients.…”
Get full text

Evolutionary accumulation modeling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance by Jessica Renz, Kazeem A. Dauda, Olav N. L. Aga, Ramon Diaz-Uriarte, Iren H. Löhr, Bjørn Blomberg, Iain G. Johnston

“…ABSTRACT Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? …”
Get full text

A Hypoxia Gene-Based Signature to Predict the Survival and Affect the Tumor Immune Microenvironment of Osteosarcoma in Children by Feng Jiang, Xiao-Lin Miao, Xiao-Tian Zhang, Feng Yan, Yan Mao, Chu-Yan Wu, Guo-Ping Zhou

“…In osteosarcoma, hypoxia promotes the malignant phenotype, which results in a cascade of immunosuppressive processes, poor prognosis, and a high risk of metastasis. …”
Get full text

Introducing CHiDO—A No Code Genomic Prediction software implementation for the characterization and integration of driven omics by Francisco González, Julián García‐Abadillo, Diego Jarquín

“…Leveraging large and diverse datasets can improve the characterization of phenotypic responses due to environmental stimuli and genomic pulses. …”
Get full text

GNN-FTuckER: A novel link prediction model for identifying suitable populations for tea varieties. by Jun Li, Bing Yang, Jiaxin Liu, Xu Wang, Zhongyuan Wu, Qiang Huang, Peng He

“…To address this issue, this paper proposes a link prediction model based on Graph Neural Networks (GNN) and tensor decomposition, named GNN-FTuckER, designed to predict the "tea suitability" relationships within the tea knowledge graph. …”
Get full text