A deep learning‐based tumor classifier directly using MS raw data

H Dong, Y Liu, WF Zeng, K Shu, Y Zhu, C Chang - Proteomics, 2020 - Wiley Online Library
Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic
Tumor Analysis Consortium (CPTAC), large‐scale mass spectrometry (MS) based proteomic …

[HTML][HTML] AI and precision oncology in clinical cancer genomics: From prevention to targeted cancer therapies-an outcomes based patient care

Z Dlamini, A Skepu, N Kim, M Mkhabele… - Informatics in Medicine …, 2022 - Elsevier
Precision medicine is the personalization of medicine to suit a specific group of people or
even an individual patient, based on genetic or molecular profiling. This can be done using …

Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer

V Sharma, A Singh, S Chauhan… - Current Drug …, 2024 - ingentaconnect.com
Drug discovery and development (DDD) is a highly complex process that necessitates
precise monitoring and extensive data analysis at each stage. Furthermore, the DDD …

Cancer bioinformatics for updating anticancer drug developments and personalized therapeutics

DY Lu, RX Qu, TR Lu, HY Wu - Reviews on recent clinical trials, 2017 - ingentaconnect.com
Background: Last two to three decades, this world witnesses a rapid progress of biomarkers
and bioinformatics technologies. Cancer bioinformatics is one of such important omics …

Subtype dependent biomarker identification and tumor classification from gene expression profiles

A Wang, N An, G Chen, L Liu, G Alterovitz - Knowledge-Based Systems, 2018 - Elsevier
Gene expression profiles are being used to categorize disease specific genes and classify
different tumor subtypes at the molecular level. Due to the inherent nature of these data …

Big data in cancer genomics

AT Maia, SJ Sammut, A Jacinta-Fernandes… - Current Opinion in …, 2017 - Elsevier
Advances in genomic technologies in the last decade have revolutionised the field of
medicine, especially in cancer, by producing a large amount of genetic information, often …

[HTML][HTML] Data mining and machine learning in cancer survival research: an overview and future recommendations

I Kaur, MN Doja, T Ahmad - Journal of Biomedical Informatics, 2022 - Elsevier
Data mining and machine learning techniques are transforming the decision-making
process in the medical world. From using nomograms and expert advice, scientists are now …

Biological convergence of cancer signatures

X Solé, N Bonifaci, N López-Bigas, A Berenguer… - PLoS …, 2009 - journals.plos.org
Gene expression profiling has identified cancer prognostic and predictive signatures with
superior performance to conventional histopathological or clinical parameters …

A systematic review of applications of machine learning in cancer prediction and diagnosis

A Sharma, R Rani - Archives of Computational Methods in Engineering, 2021 - Springer
Advancement in genome sequencing technology has empowered researchers to think
beyond their imagination. Researchers are trying their hard to fight against various genetic …

[HTML][HTML] Docsubty: SSUA review on trends in development and translation of omics signatures in cancer

W Ma, W Tang, JSL Kwok, AHY Tong, CWS Lo… - Computational and …, 2024 - Elsevier
The field of cancer genomics and transcriptomics has evolved from targeted profiling to swift
sequencing of individual tumor genome and transcriptome. The steady growth in genome …