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Zhenjiang Fan
Zhenjiang Fan
其他姓名Zhenziang Fan
Stanford Medicine
在 stanford.edu 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Using machine learning to predict ovarian cancer
M Lu, Z Fan, B Xu, L Chen, X Zheng, J Li, T Znati, Q Mi, J Jiang
International journal of medical informatics 141, 104195, 2020
1082020
Machine learning derivation of four computable 24-h pediatric sepsis phenotypes to facilitate enrollment in early personalized anti-inflammatory clinical trials
Y Qin, KF Kernan, Z Fan, HJ Park, S Kim, SW Canna, JA Kellum, RA Berg, ...
Critical Care 26 (1), 128, 2022
302022
Transcriptional programs driving shear stress-induced differentiation of kidney proximal tubule cells in culture
HJ Park, Z Fan, Y Bai, Q Ren, Y Rbaibi, KR Long, ML Gliozzi, ...
Frontiers in physiology 11, 587358, 2020
282020
3′-UTR shortening contributes to subtype-specific cancer growth by breaking stable ceRNA crosstalk of housekeeping genes
Z Fan, S Kim, Y Bai, B Diergaarde, HJ Park
Frontiers in Bioengineering and Biotechnology 8, 334, 2020
172020
The microRNA target site landscape is a novel molecular feature associating alternative polyadenylation with immune evasion activity in breast cancer
S Kim, YL Bai, Z Fan, B Diergaarde, GC Tseng, HJ Park
Briefings in Bioinformatics 22 (3), bbaa191, 2021
142021
Hyperferritinemic sepsis, macrophage activation syndrome, and mortality in a pediatric research network: a causal inference analysis
Z Fan, KF Kernan, Y Qin, S Canna, RA Berg, D Wessel, MM Pollack, ...
Critical Care 347 (2023), 2023
82023
Deep neural networks with knockoff features identify nonlinear causal relations and estimate effect sizes in complex biological systems
Z Fan, KF Kernan, A Sriram, PV Benos, SW Canna, JA Carcillo, S Kim, ...
GigaScience 12, giad044, 2023
52023
scMAPA: Identification of cell-type–specific alternative polyadenylation in complex tissues
Y Bai, Y Qin, Z Fan, RM Morrison, KN Nam, HM Zarour, R Koldamova, ...
Gigascience 11, giac033, 2022
32022
Causal inference using deep-learning variable selection identifies and incorporates direct and indirect causalities in complex biological systems
Z Fan, KF Kernan, PV Benos, GF Cooper, SW Canna, JA Carcillo, S Kim, ...
bioRxiv, 2021.07. 17.452800, 2021
22021
Alternative polyadenylation regulates patient-specific tumor growth by individualizing the MicroRNA target site landscape
S Kim, Y Bai, Z Fan, B Diergaarde, GC Tseng, HJ Park
22019
1453: FOUR COMPUTABLE 24-HOUR PEDIATRIC SEPSIS PHENOTYPES HAVE DIFFERENT INFLAMMATION PROFILES
Y Qin, Z Fan, HJ Park, J Carcillo
Critical Care Medicine 50 (1), 729, 2022
12022
Unveiling the Gut Microbiome Network Fingerprint: A Deep Learning Approach to Predict Immunotherapy Response in Melanoma Patients.
J Sun, Z Fan, A Sriram, HJ Park
bioRxiv, 2024.10. 21.619471, 2024
2024
Deep neural network learning biological condition information refines gene-expression-based cell subtypes
Z Fan, J Sun, H Thorpe, S Lee, S Kim, HJ Park
Briefings in Bioinformatics 25 (1), bbad512, 2024
2024
Elucidating complex biological interactions using computational techniques
Z Fan
University of Pittsburgh, 2023
2023
Derivation of four computable 24-hour pediatric sepsis phenotypes to facilitate personalized enrollment in early precise anti-inflammatory clinical trials
Y Qin, KF Kernan, Z Fan, HJ Park, S Kim, SW Canna, JA Kellum, RA Berg, ...
medRxiv, 2021.12. 02.21267016, 2021
2021
The microRNA target site landscape is a novel molecular feature associating alternative polyadenylation with immune evasion activity in breast cancer
HJP Soyeon Kim, YuLong Bai, Zhenjiang Fan, Brenda Diergaarde, George C Tseng
Briefings in Bioinformatics 22 (3), bbaa191, 2021
2021
Cell-type-specific alternative polyadenylation (APA) genes reveal the function of dynamic APA in complex tissues
Y Bai, Y Qin, Z Fan, RM Morrison, KN Nam, HM Zarour, R Koldamova, ...
bioRxiv, 2020.07. 30.229096, 2020
2020
Identifying genes and cell types with dynamic alternative polyadenylation in multi-cluster single-cell transcriptomics data
YL Bai, Y Qin, S Kim, Z Fan, KN Nam, R Koldamova, QS Padiath, HJ Park
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