Biomedical Engineering and Bioengineering Commons^™

An Elastic-Net Logistic Regression Approach To Generate Classifiers And Gene Signatures For Types Of Immune Cells And T Helper Cell Subsets, Arezo Torang, Paraag Gupta, David J. Klinke Ii

Faculty & Staff Scholarship

Background: Host immune response is coordinated by a variety of different specialized cell types that vary in time and location. While host immune response can be studied using conventional low-dimensional approaches, advances in transcriptomics analysis may provide a less biased view. Yet, leveraging transcriptomics data to identify immune cell subtypes presents challenges for extracting informative gene signatures hidden within a high dimensional transcriptomics space characterized by low sample numbers with noisy and missing values. To address these challenges, we explore using machine learning methods to select gene subsets and estimate gene coefficients simultaneously. Results: Elastic-net logistic regression, a type of …

Cancer Nanotechnology: Enhancing Tumor Cell Response To Chemotherapy For Hepatocellular Carcinoma Therapy, Sun Yongbing, Ma Wen, Yang Yuanyuan, He Mengxue, Li Aimin, Bai Lei, Yu Bin, Yu Zhiqiang

Faculty & Staff Scholarship

Abstract

Hepatocellular carcinoma (HCC) is one of the deadliest cancers due to its complexities, reoccurrence after surgical resection, metastasis and heterogeneity. In addition to sorafenib and lenvatinib for the treatment of HCC approved by FDA, various strategies including transarterial chemoembolization, radiotherapy, locoregional therapy and chemotherapy have been investigated in clinics. Recently, cancer nanotechnology has got great attention for the treatment of various cancers including HCC. Both passive and active targetings are progressing at a steady rate. Herein, we describe the lessons learned from pathogenesis of HCC and the understanding of targeted and non-targeted nanoparticles used for the delivery of small …