Literature DB >> 31902950

Brain Imaging Genomics: Integrated Analysis and Machine Learning.

Li Shen1, Paul M Thompson2.   

Abstract

Brain imaging genomics is an emerging data science field, where integrated analysis of brain imaging and genomics data, often combined with other biomarker, clinical and environmental data, is performed to gain new insights into the phenotypic, genetic and molecular characteristics of the brain as well as their impact on normal and disordered brain function and behavior. It has enormous potential to contribute significantly to biomedical discoveries in brain science. Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical and machine learning methods for brain imaging genomics, as well as a practical discussion on method selection for various biomedical applications.

Entities:  

Keywords:  Big data; brain imaging; genomics; machine learning; statistics

Year:  2019        PMID: 31902950      PMCID: PMC6941751          DOI: 10.1109/JPROC.2019.2947272

Source DB:  PubMed          Journal:  Proc IEEE Inst Electr Electron Eng        ISSN: 0018-9219            Impact factor:   10.961


  209 in total

1.  INTERSNP: genome-wide interaction analysis guided by a priori information.

Authors:  Christine Herold; Michael Steffens; Felix F Brockschmidt; Max P Baur; Tim Becker
Journal:  Bioinformatics       Date:  2009-10-16       Impact factor: 6.937

2.  Genetic influences on individual differences in longitudinal changes in global and subcortical brain volumes: Results of the ENIGMA plasticity working group.

Authors:  Rachel M Brouwer; Matthew S Panizzon; David C Glahn; Derrek P Hibar; Xue Hua; Neda Jahanshad; Lucija Abramovic; Greig I de Zubicaray; Carol E Franz; Narelle K Hansell; Ian B Hickie; Marinka M G Koenis; Nicholas G Martin; Karen A Mather; Katie L McMahon; Hugo G Schnack; Lachlan T Strike; Suzanne C Swagerman; Anbupalam Thalamuthu; Wei Wen; John H Gilmore; Nitin Gogtay; René S Kahn; Perminder S Sachdev; Margaret J Wright; Dorret I Boomsma; William S Kremen; Paul M Thompson; Hilleke E Hulshoff Pol
Journal:  Hum Brain Mapp       Date:  2017-06-05       Impact factor: 5.038

3.  Proper analysis of secondary phenotype data in case-control association studies.

Authors:  D Y Lin; D Zeng
Journal:  Genet Epidemiol       Date:  2009-04       Impact factor: 2.135

4.  High-order graph matching based feature selection for Alzheimer's disease identification.

Authors:  Feng Liu; Heung-Il Suk; Chong-Yaw Wee; Huafu Chen; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2013

5.  Supervised multi-view canonical correlation analysis (sMVCCA): integrating histologic and proteomic features for predicting recurrent prostate cancer.

Authors:  George Lee; Asha Singanamalli; Haibo Wang; Michael D Feldman; Stephen R Master; Natalie N C Shih; Elaine Spangler; Timothy Rebbeck; John E Tomaszewski; Anant Madabhushi
Journal:  IEEE Trans Med Imaging       Date:  2014-09-05       Impact factor: 10.048

6.  Genetic architecture of subcortical brain regions: common and region-specific genetic contributions.

Authors:  M E Rentería; N K Hansell; L T Strike; K L McMahon; G I de Zubicaray; I B Hickie; P M Thompson; N G Martin; S E Medland; M J Wright
Journal:  Genes Brain Behav       Date:  2014-10-08       Impact factor: 3.449

7.  APOE and BCHE as modulators of cerebral amyloid deposition: a florbetapir PET genome-wide association study.

Authors:  V K Ramanan; S L Risacher; K Nho; S Kim; S Swaminathan; L Shen; T M Foroud; H Hakonarson; M J Huentelman; P S Aisen; R C Petersen; R C Green; C R Jack; R A Koeppe; W J Jagust; M W Weiner; A J Saykin
Journal:  Mol Psychiatry       Date:  2013-02-19       Impact factor: 15.992

8.  FASTKD2 is associated with memory and hippocampal structure in older adults.

Authors:  V K Ramanan; K Nho; L Shen; S L Risacher; S Kim; B C McDonald; M R Farlow; T M Foroud; S Gao; H Soininen; I Kłoszewska; P Mecocci; M Tsolaki; B Vellas; S Lovestone; P S Aisen; R C Petersen; C R Jack; L M Shaw; J Q Trojanowski; M W Weiner; R C Green; A W Toga; P L De Jager; L Yu; D A Bennett; A J Saykin
Journal:  Mol Psychiatry       Date:  2014-11-11       Impact factor: 15.992

Review 9.  A Perspective of the Cross-Tissue Interplay of Genetics, Epigenetics, and Transcriptomics, and Their Relation to Brain Based Phenotypes in Schizophrenia.

Authors:  Jingyu Liu; Jiayu Chen; Nora Perrone-Bizzozero; Vince D Calhoun
Journal:  Front Genet       Date:  2018-08-23       Impact factor: 4.599

10.  A kernel machine method for detecting higher order interactions in multimodal datasets: Application to schizophrenia.

Authors:  Md Ashad Alam; Hui-Yi Lin; Hong-Wen Deng; Vince D Calhoun; Yu-Ping Wang
Journal:  J Neurosci Methods       Date:  2018-09-02       Impact factor: 2.390

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  28 in total

1.  Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease.

Authors:  Xianglian Meng; Jin Li; Qiushi Zhang; Feng Chen; Chenyuan Bian; Xiaohui Yao; Jingwen Yan; Zhe Xu; Shannon L Risacher; Andrew J Saykin; Hong Liang; Li Shen
Journal:  BMC Genomics       Date:  2020-12-29       Impact factor: 3.969

2.  LARGE-SCALE MULTIVARIATE SPARSE REGRESSION WITH APPLICATIONS TO UK BIOBANK.

Authors:  Junyang Qian; Yosuke Tanigawa; Ruilin Li; Robert Tibshirani; Manuel A Rivas; Trevor Hastie
Journal:  Ann Appl Stat       Date:  2022-07-19       Impact factor: 1.959

3.  Identifying Alzheimer's genes via brain transcriptome mapping.

Authors:  Jae Young Baik; Mansu Kim; Jingxuan Bao; Qi Long; Li Shen
Journal:  BMC Med Genomics       Date:  2022-05-19       Impact factor: 3.622

4.  Deep phenotyping for precision medicine in Parkinson's disease.

Authors:  Ann-Kathrin Schalkamp; Nabila Rahman; Jimena Monzón-Sandoval; Cynthia Sandor
Journal:  Dis Model Mech       Date:  2022-06-01       Impact factor: 5.732

5.  Exploring Brain Structural and Functional Biomarkers in Schizophrenia via Brain-Network-Constrained Multi-View SCCA.

Authors:  Peilun Song; Yaping Wang; Xiuxia Yuan; Shuying Wang; Xueqin Song
Journal:  Front Neurosci       Date:  2022-06-20       Impact factor: 5.152

6.  Interpretable temporal graph neural network for prognostic prediction of Alzheimer's disease using longitudinal neuroimaging data.

Authors:  Mansu Kim; Jaesik Kim; Jeffrey Qu; Heng Huang; Qi Long; Kyung-Ah Sohn; Dokyoon Kim; Li Shen
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2021-12

7.  A Novel Bayesian Semi-parametric Model for Learning Heritable Imaging Traits.

Authors:  Yize Zhao; Xiwen Zhao; Mansu Kim; Jingxuan Bao; Li Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2021-09-21

8.  Polygenic mediation analysis of Alzheimer's disease implicated intermediate amyloid imaging phenotypes.

Authors:  Eng Yingxuan; Xiaohui Yao; Kefei Liu; Shannon L Risacher; Andrew J Saykin; Qi Long; Yize Zhao; Li Shen
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

9.  Multi-task learning based structured sparse canonical correlation analysis for brain imaging genetics.

Authors:  Mansu Kim; Eun Jeong Min; Kefei Liu; Jingwen Yan; Andrew J Saykin; Jason H Moore; Qi Long; Li Shen
Journal:  Med Image Anal       Date:  2021-11-13       Impact factor: 8.545

10.  Progress and Research Priorities in Imaging Genomics for Heart and Lung Disease: Summary of an NHLBI Workshop.

Authors:  Donna K Arnett; Ramachandran S Vasan; Matthew Nayor; Li Shen; Gary M Hunninghake; Peter Kochunov; R Graham Barr; David A Bluemke; Ulrich Broeckel; Peter Caravan; Susan Cheng; Paul S de Vries; Udo Hoffmann; Márton Kolossváry; Huiqing Li; James Luo; Elizabeth M McNally; George Thanassoulis
Journal:  Circ Cardiovasc Imaging       Date:  2021-08-13       Impact factor: 8.589

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