Recent advances in microfluidic single-cell analysis and its applications in drug development

Y Jiao, L Gao, Y Ji, W Liu - TrAC Trends in Analytical Chemistry, 2022 - Elsevier
Cellular heterogeneity is prevalent in all cell populations. Single-cell analysis (SCA) could
unveil the heterogeneity and thus gain unique insights into complex biological processes …

Focus on Cdc42 in breast cancer: new insights, target therapy development and non-coding RNAs

Y Zhang, J Li, XN Lai, XQ Jiao, JP Xiong, LX Xiong - Cells, 2019 - mdpi.com
Breast cancer is the most common malignant tumors in females. Although the conventional
treatment has demonstrated a certain effect, some limitations still exist. The Rho guanosine …

Cdc42: a novel regulator of insulin secretion and diabetes-associated diseases

QY Huang, XN Lai, XL Qian, LC Lv, J Li, J Duan… - International journal of …, 2019 - mdpi.com
Cdc42, a member of the Rho GTPases family, is involved in the regulation of several cellular
functions including cell cycle progression, survival, transcription, actin cytoskeleton …

Concepts driving pharmacogenomics implementation into everyday healthcare

J Giri, AM Moyer, SJ Bielinski… - Pharmacogenomics and …, 2019 - Taylor & Francis
Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the
greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge …

A Supervised Learning Identification System for Prognosis of Breast Cancer

V Rawat, K Gulati, U Kaur, JK Seth… - Mathematical …, 2022 - Wiley Online Library
Breast cancer is one of the most dangerous cancers, accounting for a large number of
fatalities each year. It is the leading cause of mortality among women globally. It is getting a …

Molecular classification models for triple negative breast cancer subtype using machine learning

R Bissanum, S Chaichulee, R Kamolphiwong… - Journal of Personalized …, 2021 - mdpi.com
Triple negative breast cancer (TNBC) lacks well-defined molecular targets and is highly
heterogenous, making treatment challenging. Using gene expression analysis, TNBC has …

Supervised machine learning predictive analytics for triple-negative breast cancer death outcomes

Y Xu, L Ju, J Tong, C Zhou, J Yang - OncoTargets and therapy, 2019 - Taylor & Francis
Objective To use machine learning algorithms to predict the death outcomes of patients with
triple-negative breast cancer, 5 years after discharge. Methods 1570 stage I-III breast cancer …

Development of an Artificial intelligence Breast Cancer diagnostic tool

RSP de Castro - 2023 - search.proquest.com
Breast cancer poses a global healthcare challenge due to its prevalence and multifactorial
etiology. Despite advances in early detection and treatment, therapeutic approaches like …

Review of Existing Systems In Biomedical Using Deep Learning Algorithms

M Sowmiya, C Thilagavathi, M Rajeswari… - Handbook of Deep …, 2021 - taylorfrancis.com
In recent days, many researchers focus on interdisciplinary research work to solve various
research problems. One such interdisciplinary research work is the implementation of deep …

[PDF][PDF] Research Article A Supervised Learning Identification System for Prognosis of Breast Cancer

V Rawat, K Gulati, U Kaur, JK Seth, V Solanki… - 2022 - academia.edu
Breast cancer is one of the most dangerous cancers, accounting for a large number of
fatalities each year. It is the leading cause of mortality among women globally. It is getting a …