Logistic regression with adaptive sparse group lasso penalty and its application in acute leukemia diagnosis

J Li, K Liang, X Song - Computers in Biology and Medicine, 2022 - Elsevier
Cancer diagnosis based on gene expression profile data has attracted extensive attention in
computational biology and medicine. It suffers from three challenges in practical …

Ampullary Adenocarcinoma: A Review of the Mutational Landscape and Implications for Treatment

V Tsagkalidis, RC Langan, BL Ecker - Cancers, 2023 - mdpi.com
Simple Summary Ampullary tumors are rare malignancies of the upper gastrointestinal tract.
Histologic, immunohistochemical and, most recently, genomic biomarkers have been used …

Genome-derived classification signature for ampullary adenocarcinoma to improve clinical cancer care

S Chakraborty, BL Ecker, K Seier, VG Aveson… - Clinical Cancer …, 2021 - AACR
Purpose: The clinical behavior of ampullary adenocarcinoma varies widely. Targeted tumor
sequencing may better define biologically distinct subtypes to improve diagnosis and …

Mining mutation contexts across the cancer genome to map tumor site of origin

S Chakraborty, A Martin, Z Guan, CB Begg… - Nature …, 2021 - nature.com
The vast preponderance of somatic mutations in a typical cancer are either extremely rare or
have never been previously recorded in available databases that track somatic mutations …

Genome-derived ampullary adenocarcinoma classifier and postresection prognostication

BL Ecker, K Seier, AM Eckhoff, GN Tortorello… - JAMA …, 2024 - jamanetwork.com
Importance Ampullary adenocarcinoma (AA) is characterized by clinical and genomic
heterogeneity. A previously developed genomic classifier defined biologically distinct …

Genome-driven cancer site characterization: An overview of the hidden genome model

S Chakraborty - Modern Inference Based on Health-Related Markers, 2024 - Elsevier
A large and growing body of research has documented strong links between somatic
mutations and different cancer types. This has put forward an emerging field aiming to …

Topical hidden genome: discovering latent cancer mutational topics using a Bayesian multilevel context-learning approach

S Chakraborty, Z Guan, CB Begg, R Shen - Biometrics, 2024 - academic.oup.com
Inferring the cancer-type specificities of ultra-rare, genome-wide somatic mutations is an
open problem. Traditional statistical methods cannot handle such data due to their ultra-high …

Identifying somatic fingerprints of cancers defined by germline and environmental risk factors

S Chakraborty, Z Guan, CE Kostrzewa… - Genetic …, 2024 - Wiley Online Library
Numerous studies over the past generation have identified germline variants that increase
specific cancer risks. Simultaneously, a revolution in sequencing technology has permitted …

Predicting cancer risk from germline whole-exome sequencing data using a novel context-based variant aggregation approach

Z Guan, CB Begg, R Shen - Cancer Research Communications, 2023 - AACR
Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic
contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new …

Influence of genomic characteristics on the optimization of models for tumor cell-of-origin prediction

P Štancl - 2024 - repozitorij.pmf.unizg.hr
Sažetak Identifying the cell-of-origin (COO) for tumors of unknown primary site is crucial for
selecting effective therapies, but the heterogeneity and unique genomic profiles of these …