activity
20202026
most citedComparing Lasso and Adaptive Lasso in High-Dimensional Data: A Genetic Survival Analysis in Triple-Negative Breast Cancer

2 citations · 4 across the 9 of their papers we have counts for

collaborators

11 papers

stat.ME2026

Nonparametric Estimation of Event-Free Survival for Data with Left-Truncated Death and Intermittently Assessed Nonfatal Events

Han Lu, Xianghua Luo, Yifei Sun +6

In certain clinical settings, patients diagnosed with a disease of interest are at risk for death as well as a serious nonfatal event, and interest lies in event-free survival (EFS…

q-bio.MN2026

MERLIN-SUITE: Probabilistic modular GRN inference from multi-omics data integrating regulatory priors and transcription factor activity

Suvojit Hazra, Marina Kotvanova, Kirstan Gimse +1

Accurately reconstructing gene regulatory networks (GRNs) is essential for understanding transcriptional processes in development and disease. MERLIN-SUITE (https://github.com/Roy-…

q-bio.MN2026

scMTNI: Leveraging cellular trajectory and context to infer dynamic GRNs from single-cell multi-omics data

Suvojit Hazra, Chandrani Kumari, Sushmita Roy

Transcriptional gene regulatory networks (GRNs) depict the directed relationships between regulators and target genes, determining gene expression patterns in a cell-type-specific…

q-bio.MN2026

Modeling Dynamics, Cell Type Specificity, and Perturbations in Gene Regulatory Networks

Junha Shin, Spencer Halberg-Spencer, Yuda Liu +3

Gene regulatory networks (GRNs) define the regulatory relationships among molecules such as transcription factors, chromatin remodelers, and target genes. GRNs play a critical role…

cs.LG2025★ 1 cited

The Target Polish: A New Approach to Outlier-Resistant Non-Negative Matrix Factorization

Paul Fogel, Christophe Geissler, George Luta

This paper introduces the "Target Polish," a robust and computationally efficient framework for Non-Negative Matrix Factorization (NMF). Although conventional weighted NMF approach…

stat.AP2025

Bayesian Regression Analysis with the Drift-Diffusion Model

Zekai Jin, Yaakov Stern, Seonjoo Lee

The Drift-Diffusion Model (DDM) is widely used in neuropsychological studies to understand the decision process by incorporating both reaction times and subjects' responses. Variou…

stat.ME2025

Demographic Parity-aware Individualized Treatment Rules

Wenhai Cui, Wen Su, Xiaodong Yan +2

There has been growing interest in developing optimal individualized treatment rules (ITRs) in various fields, such as precision medicine, business decision-making, and social welf…

stat.ME2024★ 2 cited

Comparing Lasso and Adaptive Lasso in High-Dimensional Data: A Genetic Survival Analysis in Triple-Negative Breast Cancer

Pilar González-Barquero, Rosa E. Lillo, Álvaro Méndez-Civieta

In high-dimensional survival analysis, effective variable selection is crucial for both model interpretation and predictive performance. This paper investigates Cox regression with…

stat.AP2023★ 1 cited

Bayesian Nonparametric Clustering with Feature Selection for Spatially Resolved Transcriptomics Data

Bencong Zhu, Guanyu Hu, Yang Xie +3

The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profilin…

stat.ME2022

Sequential monitoring using the Second Generation P-Value with Type I error controlled by monitoring frequency

Jonathan J. Chipman, Robert A. Greevy, Lindsay Mayberry +1

Many adaptive monitoring schemes adjust the required evidence toward a hypothesis to control Type I error. This shifts focus away from determining scientific relevance with an unco…

q-bio.PE2020

Inferring high-resolution human mixing patterns for disease modeling

Dina Mistry, Maria Litvinova, Ana Pastore y Piontti +12

Mathematical and computational modeling approaches are increasingly used as quantitative tools in the analysis and forecasting of infectious disease epidemics. The growing need for…