🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Kefei Liu

Suzhou University of Science and Technology

ORCID: 0000-0003-0737-9976

Also affiliated with Tianjin Energy Investment Group (China)

Biochemistry, Genetics and Molecular BiologyNeuroscienceMathematics

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile
0Author DataRank

Indexed papers

0in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 9 papers. Top paper: “Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules”.

Tissue-specific network-based genome wide study of amygdala imaging phenotypes to identify functional interaction modules

Bioinformatics(2017)10.1093/bioinformatics/btx344
N/A
0.489DataRank · unranked
25 citations

Jingwen Yan, Kefei Liu, Sungeun Kim, Kwangsik Nho, Shannon L. Risacher +6 more

A structural enriched functional network: An application to predict brain cognitive performance

Medical Image Analysis(2021)10.1016/j.media.2021.102026
N/A
0.483DataRank · unranked
24 citations

Jingxuan Bao, Kefei Liu, Bo‐yong Park, Hyunjin Park, Jae Young Baik +2 more

Associating Multi-Modal Brain Imaging Phenotypes and Genetic Risk Factors via a Dirty Multi-Task Learning Method

IEEE Transactions on Medical Imaging(2020)10.1109/tmi.2020.2995510
N/A
0DataRank · unranked
44 citations

Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han +3 more

Identifying diagnosis-specific genotype–phenotype associations via joint multitask sparse canonical correlation analysis and classification

Bioinformatics(2020)10.1093/bioinformatics/btaa434
N/A
0DataRank · unranked
38 citations

Fang Liu, Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han +5 more

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

Medical Image Analysis(2021)10.1016/j.media.2021.102297
N/A
0DataRank · unranked
29 citations

Eun Jeong Min, Kefei Liu, Jingwen Yan, Andrew J. Saykin, Jason H. Moore +3 more

Deep multiview learning to identify imaging-driven subtypes in mild cognitive impairment

BMC Bioinformatics(2022)10.1186/s12859-022-04946-x
N/A
0DataRank · unranked
15 citations

Mansu Kim, Xiaohui Yao, Kefei Liu, Qi Long, Li Shen +2 more

Preference Matrix Guided Sparse Canonical Correlation Analysis for Genetic Study of Quantitative Traits in Alzheimer’s Disease

2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)(2022)10.1109/bibm55620.2022.9995342
N/A
0DataRank · unranked
0 citations

Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Yuhan Cui +7 more

Preference matrix guided sparse canonical correlation analysis for mining brain imaging genetic associations in Alzheimer's disease

Methods(2023)10.1016/j.ymeth.2023.07.007
N/A
0DataRank · unranked
6 citations

Jingxuan Bao, Kefei Liu, Shu Yang, Zixuan Wen, Junhao Wen +8 more

Detecting genetic associations with brain imaging phenotypes in Alzheimer’s disease via a novel structured SCCA approach

Medical Image Analysis(2020)10.1016/j.media.2020.101656
N/A
0DataRank · unranked
87 citations

Kefei Liu, Xiaohui Yao, Shannon L. Risacher, Junwei Han, Andrew J. Saykin +3 more