Article
Computer Science, Artificial Intelligence
Zheng Lv, Kai Chen, Tai Zhang, Jun Zhao, Wei Wang
Summary: This paper proposes a multi-feature generation network-based imputation algorithm, which transforms industrial data sequence into Gaussian mixture distribution and imputes the multi-scale features. The experimental results show that the proposed method can reduce the complexity of data generation and improve the imputation accuracy, providing an effective solution for the problem of industrial data missing in the case of high missing rate.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Genetics & Heredity
Alison R. Barton, Maxwell A. Sherman, Ronen E. Mukamel, Po-Ru Loh
Summary: This study leveraged haplotype sharing in the UK Biobank to impute exome-wide variants and identified significant associations involving rare protein-altering variants. The research revealed significant associations in multiple genes and proposed allelic series containing multiple "likely-causal" variants.
Article
Genetics & Heredity
Mi Yeong Hwang, Nak-Hyeon Choi, Hong Hee Won, Bong-Jo Kim, Young Jin Kim
Summary: Genotype imputation is crucial for association-mapping and identifying missed variants. A population-specific or multi-ethnic reference panel improves imputation accuracy. The KRG project identified variants in Korean participants and outperformed other reference panels. Using a population-specific reference panel and meta-imputation allows for accurate imputation of rare variants.
FRONTIERS IN GENETICS
(2022)
Article
Genetics & Heredity
Robin J. Hofmeister, Diogo M. Ribeiro, Simone Rubinacci, Olivier Delaneau
Summary: SHAPEIT5, a new phasing method, accurately processes large sequencing datasets and improves imputation accuracy by generating reference panels of haplotypes. The method was applied to UK Biobank data, which resulted in the identification of 549 genes with compound heterozygous loss-of-function events. The use of UK Biobank as a reference panel, coupled with SHAPEIT5 phasing, further enhances genotype imputation accuracy.
Article
Multidisciplinary Sciences
Jaeyong Choi, Sungjae Kim, Juhyun Kim, Ho-Young Son, Seong-Keun Yoo, Chang-Uk Kim, Young Jun Park, Sungji Moon, Bukyoung Cha, Min Chul Jeon, Kyunghyuk Park, Jae Moon Yun, Belong Cho, Namcheol Kim, Changhoon Kim, Nak-Jung Kwon, Young Joo Park, Fumihiko Matsuda, Yukihide Momozawa, Michiaki Kubo, Hyun-Jin Kim, Jin-Ho Park, Jeong-Sun Seo, Jong-Il Kim, Sun-Wha Im
Summary: In order to advance global precision medicine, we created a reference panel consisting of over 11,000 Asian individuals. Using this panel, we discovered 39 previously unidentified associations, with over half of the variants being specific to East Asian populations. We also found genes related to traits such as height and body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects.
Article
Genetics & Heredity
Yichen Si, Brett Vanderwerff, Sebastian Zollner
Summary: Genotype imputation is crucial in human genetic studies, but current algorithms may have model misspecifications that limit the accurate imputation of rare variants. The probability of falsely imputed minor alleles decreases with reference sample size, but the proportion of erroneously imputed minor alleles depends on the allele count in the reference sample.
Article
Psychology, Biological
Seon-Kyeong Jang, Luke Evans, Allison Fialkowski, Donna K. Arnett, Allison E. Ashley-Koch, Kathleen C. Barnes, Diane M. Becker, Joshua C. Bis, John Blangero, Eugene R. Bleecker, Meher Preethi Boorgula, Donald W. Bowden, Jennifer A. Brody, Brian E. Cade, Brenda W. Campbell Jenkins, April P. Carson, Sameer Chavan, L. Adrienne Cupples, Brian Custer, Scott M. Damrauer, Sean P. David, Mariza de Andrade, Carla L. Dinardo, Tasha E. Fingerlin, Myriam Fornage, Barry I. Freedman, Melanie E. Garrett, Sina A. Gharib, David C. Glahn, Jeffrey Haessler, Susan R. Heckbert, John E. Hokanson, Lifang Hou, Shih-Jen Hwang, Matthew C. Hyman, Renae Judy, Anne E. Justice, Robert C. Kaplan, Sharon L. R. Kardia, Shannon Kelly, Wonji Kim, Charles Kooperberg, Daniel Levy, Donald M. Lloyd-Jones, Ruth J. F. Loos, Ani W. Manichaikul, Mark T. Gladwin, Lisa Warsinger Martin, Mehdi Nouraie, Olle Melander, Deborah A. Meyers, Courtney G. Montgomery, Kari E. North, Elizabeth C. Oelsner, Nicholette D. Palmer, Marinelle Payton, Anna L. Peljto, Patricia A. Peyser, Michael Preuss, Bruce M. Psaty, Dandi Qiao, Daniel J. Rader, Nicholas Rafaels, Susan Redline, Robert M. Reed, Alexander P. Reiner, Stephen S. Rich, Jerome I. Rotter, David A. Schwartz, Aladdin H. Shadyab, Edwin K. Silverman, Nicholas L. Smith, J. Gustav Smith, Albert V. Smith, Jennifer A. Smith, Weihong Tang, Kent D. Taylor, Marilyn J. Telen, Ramachandran S. Vasan, Victor R. Gordeuk, Zhe Wang, Kerri L. Wiggins, Lisa R. Yanek, Ivana V. Yang, Kendra A. Young, Kristin L. Young, Yingze Zhang, Dajiang J. Liu, Matthew C. Keller, Scott Vrieze
Summary: Rare genetic variants contribute significantly to the heritability of smoking behavior.
NATURE HUMAN BEHAVIOUR
(2022)
Article
Economics
Wei Lan, Xuerong Chen, Tao Zou, Chih-Ling Tsai
Summary: This study introduces an innovative method for imputing missing data in high missing-rate covariates inspired by semi-supervised learning concept, without imposing any model assumptions, providing closed-form imputation for continuous covariates, and also applicable for discrete covariates.
JOURNAL OF BUSINESS & ECONOMIC STATISTICS
(2022)
Article
Oncology
Cheng Wang, Juncheng Dai, Na Qin, Jingyi Fan, Hongxia Ma, Congcong Chen, Mingxing An, Jing Zhang, Caiwang Yan, Yayun Gu, Yuan Xie, Yuanlin He, Yue Jiang, Meng Zhu, Ci Song, Tao Jiang, Jia Liu, Jun Zhou, Nanxi Wang, Tingting Hua, Shuang Liang, Lu Wang, Jing Xu, Rong Yin, Liang Chen, Lin Xu, Guangfu Jin, Dongxin Lin, Zhibin Hu, Hongbing Shen
Summary: This study presents the largest whole-genome sequencing study of NSCLC in individuals of Chinese ancestry, identifying common and low-frequency loci and cancer predisposition genes associated with NSCLC risk. The study also highlights the significant effect of promoter variants on NSCLC risk. These findings have been validated in independent case-control and prospective cohort studies.
Article
Computer Science, Artificial Intelligence
Feng Zhao, Yan Lu, Xinning Li, Lina Wang, Yingjie Song, Deming Fan, Caiming Zhang, Xiaobo Chen
Summary: Credit risk assessment is crucial for banks in loan approval and risk management. However, missing credit risk data can significantly reduce the effectiveness of the assessment model. In this paper, a novel method named MGAIN is proposed to accurately predict missing data through subset selection and multiple imputation strategy, improving the accuracy of the imputation model.
APPLIED SOFT COMPUTING
(2022)
Article
Engineering, Multidisciplinary
Han Honggui, Sun Meiting, Wu Xiaolong, Li Fangyu
Summary: This article proposes a double-cycle weighted imputation (DCWI) method to deal with multiple missing patterns in the wastewater treatment process. The method maximizes the utilization of available information to improve imputation accuracy and experimental results show its superiority over comparison methods.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2022)
Article
Biochemical Research Methods
Weijia Kong, Bertrand Jern Han Wong, Harvard Wai Hann Hui, Kai Peng Lim, Yulan Wang, Limsoon Wong, Wilson Wen Bin Goh
Summary: Missing values can have negative effects on data analysis and machine learning model development. A new mixed-model method called ProJect (Protein inJection) is proposed for missing value imputation, which is an improvement over existing methods. ProJect consistently outperforms other methods in tests on various high-throughput data types. It handles different types of missing values and achieves more accurate and reliable imputation outcomes.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
Soohwan Jeong, Chonghyo Joo, Jongkoo Lim, Hyungtae Cho, Sungsu Lim, Junghwan Kim
Summary: Missing values in lubricant formulation data are common due to the complexity of lubricant manufacturing. To obtain meaningful information, such as correlations and patterns, it is crucial to impute missing values using statistical analysis and data mining. Traditional methods neglect the latent structure and only consider feature information, while the proposed graph-based imputation method (GBIM) considers both feature information and data point relations, achieving higher imputation accuracy compared to traditional methods.
COMPUTERS IN INDUSTRY
(2023)
Article
Computer Science, Artificial Intelligence
Xu Zhou, Xiaofeng Liu, Gongjin Lan, Jian Wu
Summary: Air quality is a major global concern, leading to the deployment of intelligent monitoring networks in various places. However, these networks often have missing data, posing challenges for air quality studies. The use of generative adversarial networks (GAN) has shown promising results for data imputation in air quality monitoring, especially when combining data from different owners without sharing detailed information. Results from a federated GAN method show improved model performance and stability across collaborating participants.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Agriculture, Dairy & Animal Science
Jose Luis Gualdron Duarte, Can Yuan, Ann-Stephan Gori, Gabriel C. M. Moreira, Haruko Takeda, Wouter Coppieters, Carole Charlier, Michel Georges, Tom Druet
Summary: This study conducted a genome-wide association study for traits related to body size and muscular development in Belgian Blue beef cattle and identified 37 genome-wide significant quantitative trait loci (QTL). Pleiotropic effects were observed in most of the identified QTL regions, and a multiple-trait approach was applied to refine the candidate variant sets. Strong candidate genes and causal variants related to growth and height were identified.
GENETICS SELECTION EVOLUTION
(2023)
Article
Plant Sciences
Haixiao Dong, He Li, Yingjie Xue, Shengzhong Su, Shipeng Li, Xiaohui Shan, Hongkui Liu, Nan Jiang, Xuyang Wu, Zhiwu Zhang, Yaping Yuan
Summary: A novel colorless maize mutant was identified and characterized, showing reduced pigmentation throughout its life cycle. The E183K mutation in maize chalcone synthase C2 was identified as the causal mutation for the colorless phenotype. This mutation led to protein aggregation of chalcone synthase, providing insight into protein aggregation in plants.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Genetics & Heredity
Jiabo Wang, Zhiwu Zhang
Summary: Genome-wide association study (GWAS) and genomic prediction/selection (GP/GS) are two essential tasks in genomic research. GAPIT, a widely-used integrated tool, has recently introduced multi-locus test methods to enhance statistical power and prediction accuracy.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2021)
Letter
Biochemistry & Molecular Biology
Xianra Li, Tingting Guo, Guihua Bai, Zhiwu Zhang, Deven See, Juliet Marshall, Kimberly A. Garland-Campbell, Jianming Yu
Article
Plant Sciences
Lance F. Merrick, Adrienne B. Burke, Zhiwu Zhang, Arron H. Carter
Summary: This study aimed to dissect the genetic architecture of seedling emergence in wheat using one multi-trait genome-wide association study (MT-GWAS) and three single-trait GWAS (ST-GWAS) models. The ST-GWAS models identified 107 significant markers across 19 chromosomes, while the MT-GWAS identified 82 significant markers across 14 chromosomes. The FarmCPU and BLINK models were able to identify both small effect markers and large effect markers on chromosome 5A.
FRONTIERS IN PLANT SCIENCE
(2022)
Review
Genetics & Heredity
Karansher S. Sandhu, Lance F. Merrick, Sindhuja Sankaran, Zhiwu Zhang, Arron H. Carter
Summary: The adoption of genomic selection and phenomics tools in plant breeding programs has significantly increased in the past decade. Genomic selection has shown potential in selecting superior genotypes with high precision and accelerating the breeding cycle, while phenomics aims to alleviate phenotyping bottlenecks and explore new large-scale phenotyping and data acquisition methods. This review discusses the lessons learned from genomic selection and phenomics in six self-pollinated crops and their implementation schemes, with a focus on rice, wheat, soybean, common bean, chickpea, and groundnut.
FRONTIERS IN GENETICS
(2022)
Article
Genetics & Heredity
Ruicai Long, Fan Zhang, Zhiwu Zhang, Mingna Li, Lin Chen, Xue Wang, Wenwen Liu, Tiejun Zhang, Long-Xi Yu, Fei He, Xueqian Jiang, Xijiang Yang, Changfu Yang, Zhen Wang, Junmei Kang, Qingchuan Yang
Summary: This study reported the chromosome-level genome sequence and genomic variation database of Zhongmu-4, a widely cultivated alfalfa cultivar in China, as well as the polymorphic genes associated with agronomic traits. The expansion of gene families and increase of repetitive elements observed in Zhongmu-4 genome may contribute to its larger genome size compared to Medicago truncatula. The population structure analysis revealed the influence of geography on the genetic divergence of alfalfa. The findings of this study will facilitate genetic research and genomics-assisted breeding for alfalfa variety improvement.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2022)
Review
Food Science & Technology
Yang Hu, Stephanie M. Sjoberg, Chunpen (James) Chen, Amber L. Hauvermale, Craig F. Morris, Stephen R. Delwiche, Ashley E. Cannon, Camille M. Steber, Zhiwu Zhang
Summary: This review examines the application, limitations, and potential alternatives to the Hagberg-Perten falling number (FN) method used in the global wheat industry. The FN test indirectly detects the presence of alpha-amylase, which is responsible for starch degradation. Low FN/high alpha-amylase in wheat grains results in poor end-product quality and significant losses for various stakeholders. The FN method has limitations such as sampling variability, high cost, labor intensiveness, destructive nature, and inability to differentiate between different causes of low FN. Seeking faster, cheaper, and more accurate alternatives can improve breeding and avoid inadvertent mixing of high- and low-FN grain, thus preserving the value of wheat grain.
COMPREHENSIVE REVIEWS IN FOOD SCIENCE AND FOOD SAFETY
(2022)
Article
Agriculture, Dairy & Animal Science
Chun-Peng J. Chen, Gota Morota, Kiho Lee, Zhiwu Zhang, Hao Cheng
Summary: Precision livestock farming in the swine industry focuses on using computer vision technology to automate monitoring pig activity, but the performance is highly dependent on the quality of imagery features and requires intensive effort in labeling ground truths for training datasets.
JOURNAL OF ANIMAL SCIENCE
(2022)
Article
Agronomy
Chenggen Chu, Shichen Wang, Jackie C. Rudd, Amir M. H. Ibrahim, Qingwu Xue, Ravindra N. Devkota, Jason A. Baker, Shannon Baker, Bryan Simoneaux, Geraldine Opena, Haixiao Dong, Xiaoxiao Liu, Kirk E. Jessup, Ming-Shun Chen, Kele Hui, Richard Metz, Charles D. Johnson, Zhiwu S. Zhang, Shuyu Liu
Summary: Using genome-wide association studies and high throughput genotyping based on sequencing techniques can improve the accuracy of predicting and selecting new varieties using imbalanced historical yield data.
MOLECULAR BREEDING
(2022)
Article
Plant Sciences
William Wesley Crump, Cameron Peace, Zhiwu Zhang, Per McCord
Summary: This study aims to improve fruit cracking incidence and fruit firmness in sweet cherry through DNA-informed breeding. Four stable QTLs related to fruit cracking and firmness were identified, and the ancestral sources of functional SNP haplotypes were traced.
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Multidisciplinary Sciences
Yao Zhou, Zhiyang Zhang, Zhigui Bao, Hongbo Li, Yaqing Lyu, Yanjun Zan, Yaoyao Wu, Lin Cheng, Yuhan Fang, Kun Wu, Jinzhe Zhang, Hongjun Lyu, Tao Lin, Qiang Gao, Surya Saha, Lukas Mueller, Zhangjun Fei, Thomas Stadler, Shizhong Xu, Zhiwu Zhang, Doug Speed, Sanwen Huang
Summary: Constructing a graph pangenome of tomato can improve the estimation of heritability for complex traits, identify more causal structural variants, and facilitate the identification of genetic factors underlying agronomically important traits. This study advances our understanding of the heritability of complex traits and demonstrates the power of the graph pangenome in crop breeding.
Article
Plant Sciences
Fan Zhang, Junmei Kang, Ruicai Long, Mingna Li, Yan Sun, Fei He, Xueqian Jiang, Changfu Yang, Xijiang Yang, Jie Kong, Yiwen Wang, Zhen Wang, Zhiwu Zhang, Qingchuan Yang
Summary: Fall dormancy (FD) is a crucial trait for alfalfa cultivar selection. We conducted genomic prediction of FD using machine learning methods and achieved high prediction accuracy.
HORTICULTURE RESEARCH
(2023)
Article
Agriculture, Multidisciplinary
Zhou Tang, Meinan Wang, Michael Schirrmann, Xianran Li, Robert Brueggeman, Sindhuja Sankaran, Arron H. Carter, Michael O. Pumphrey, Yang Hu, Xianming Chen, Zhiwu Zhang
Summary: In this study, a neural network-based image classifier called RustNet was developed to efficiently monitor wheat fields for stripe rust. The model uses deep learning to process images and videos captured from affordable devices, enabling high-throughput pheno-typing for early detection of rust and improved control efficiency.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Mycology
Y. P. Fu, Y. T. Dai, K. W. T. Chethana, Z. H. Li, L. Sun, C. T. Li, H. L. Yu, R. H. Yang, Q. Tan, D. P. Bao, Y. J. Deng, S. X. Wang, Y. F. Wang, F. H. Tian, L. L. Qi, L. L. Shu, P. S. Jia, L. C. Chen, M. Y. Chen, Q. X. Hu, H. Tan, T. T. Song, Z. W. Zhang, G. Bonito, G. Zervakis, S. J. Xiao, K. D. Hyde, Y. Li, X. H. Yuan
Summary: This study presents high-quality genomes, transcriptomes, and re-sequencing data of edible and medicinal mushrooms, and constructs an integrated omics database (MushDB) for a better understanding of mushroom domestication. Using multi-omics data, the researchers identified potential functional genes contributing to mushroom domestication, including genes involved in starch and sucrose metabolism and mitogen-activated protein kinase signaling pathway. The function of one key gene in low temperature adaptation and cultivation environment was validated using CRISPR/Cas9 system.
Article
Multidisciplinary Sciences
Ying Wu, Fan Lin, Yao Zhou, Jie Wang, Shuai Sun, Bin Wang, Zhibin Zhang, Guo Li, Xiuyun Lin, Xutong Wang, Yue Sun, Qianli Dong, Chunming Xu, Lei Gong, Jonathan F. Wendel, Zhiwu Zhang, Bao Liu
Summary: This study found that homoeologous exchanges (HEs) in allopolyploids can lead to extensive genomic variation, affecting known-function genes and their complex genetic interactions, thereby creating extraordinary phenotypic diversity at the population level.
NATIONAL SCIENCE REVIEW
(2021)
