James P. Long

According to our database, James P. Long authored at least 12 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Partial Causal Structure Learning for Valid Selective Conformal Inference under Interventions.

Amir Asiaee, Kavey Aryan, James P. Long

CoRR, March, 2026

2025

Causal Discovery with Mixed Latent Confounding via Precision Decomposition.

Amir Asiaee, Samhita Pal, James O'Quinn, James P. Long

CoRR, December, 2025

Causal models and prediction in cell line perturbation experiments.

James P. Long, Yumeng Yang, Shohei Shimizu, Thong Pham, Kim-Anh Do

BMC Bioinform., December, 2025

DAG DECORation: Continuous Optimization for Structure Learning under Hidden Confounding.

Samhita Pal, James O'Quinn, Kaveh Aryan, Heather Pua, James P. Long, Amir Asiaee

CoRR, October, 2025

AUPRC: a metric for evaluating the performance of <i>in-silico</i> perturbation methods in identifying differentially expressed genes.

Hongxu Zhu, Amir Asiaee, Leila Azinfar, Jun Li, Han Liang, Ehsan Irajizad, Kim-Anh Do, James P. Long

Briefings Bioinform., September, 2025

Robust Learning on Noisy Graphs via Latent Space Constraints with External Knowledge.

Chunhui Gu, Mohammad Sadegh Nasr, James P. Long, Kim-Anh Do, Ehsan Irajizad

CoRR, July, 2025

Digital twins in healthcare: a comprehensive review and future directions.

Hamid Khoshfekr Rudsari, Becky Tseng, Hongxu Zhu, Lulu Song, Chunhui Gu, Abhishikta Roy, Ehsan Irajizad, Joseph Butner, James P. Long, Kim-Anh Do

Frontiers Digit. Health, 2025

Rank-based learning: a novel high-throughput algorithm resilient to missing data and effective for datasets with small sample size.

Lulu Song, Hamid Khoshfekr Rudsari, Johannes F. Fahrmann, Jody V. Vykoukal, Sam Hanash, James P. Long, Kim-Anh Do, Ehsan Irajizad

Briefings Bioinform., 2025

2023

A unified mediation analysis framework for integrative cancer proteogenomics with clinical outcomes.

Licai Huang, James P. Long, Ehsan Irajizad, James D. Doecke, Kim-Anh Do, Min Jin Ha

Bioinform., January, 2023

2022

Sample selection bias in evaluation of prediction performance of causal models.

James P. Long, Min Jin Ha

Stat. Anal. Data Min., 2022

Application of Artificial Intelligence to Plasma Metabolomics Profiles to Predict Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer.

Ehsan Irajizad, Ranran Wu, Jody V. Vykoukal, Eunice Murage, Rachelle Spencer, Jennifer B. Dennison, Stacy Moulder, Elizabeth Ravenberg, Bora Lim, Jennifer Litton, Debu Tripathy, Vicente Valero, Senthil Damodaran, Gaiane M. Rauch, Beatriz E. Adrada, Rosalind Candelaria, Jason B. White, Abenaa Brewster, Banu Arun, James P. Long, Kim-Anh Do, Sam Hanash, Johannes F. Fahrmann

Frontiers Artif. Intell., 2022

2020

A flexible procedure for mixture proportion estimation in positive-unlabeled learning.

Zhenfeng Lin, James P. Long

Stat. Anal. Data Min., 2020