AIMC Topic: Neoplasm Proteins

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Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.

Scientific reports May 11, 2015
The number of mutated genes in cancer cells is far larger than the number of mutations that drive cancer. The difficulty this creates for identifying relevant alterations has stimulated the development of various computational approaches to distingui...
Mutation Genes, Neoplasm Humans Machine Learning Animals United States Databases, Genetic Neoplasm Proteins
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Prediction of cancer proteins by integrating protein interaction, domain frequency, and domain interaction data using machine learning algorithms.

BioMed research international Mar 17, 2015
Many proteins are known to be associated with cancer diseases. It is quite often that their precise functional role in disease pathogenesis remains unclear. A strategy to gain a better understanding of the function of these proteins is to make use of...
Protein Structure, Tertiary Animals Humans Sequence Analysis, Protein Neoplasms Machine Learning Databases, Protein Algorithms Neoplasm Proteins
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Combining multi-parametric MRI radiomics features with tumor abnormal protein to construct a machine learning-based predictive model for prostate cancer.

Scientific reports Jul 2, 2025
This study aims to investigate the diagnostic value of integrating multi-parametric magnetic resonance imaging (mpMRI) radiomic features with tumor abnormal protein (TAP) and clinical characteristics for diagnosing prostate cancer. A cohort of 109 pa...
Humans Machine Learning Aged Neoplasm Proteins Prostatic Neoplasms Prostate-Specific Antigen Multiparametric Magnetic Resonance Imaging Radiomics Male Middle Aged Magnetic Resonance Imaging
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TPD52 as a Therapeutic Target Identified by Machine Learning Shapes the Immune Microenvironment in Breast Cancer.

Journal of cellular and molecular medicine Jan 1, 2025
Breast cancer (BRCA) is one of the most common malignancies and a leading cause of cancer-related mortality among women globally. Despite advances in diagnosis and treatment, the heterogeneity of BRCA presents significant challenges for effective man...
Neoplasm Proteins Single-Cell Analysis Computational Biology Gene Expression Regulation, Neoplastic Tumor Microenvironment Biomarkers, Tumor Gene Expression Profiling Cell Line, Tumor Humans Machine Learning Prognosis Female Breast Neoplasms
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Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network.

Briefings in bioinformatics Sep 2, 2021
Triple-negative breast cancer (TNBC) has been a challenging breast cancer subtype for oncological therapy. Normally, it can be classified into different molecular subtypes. Accurate and stable classification of the six subtypes is essential for perso...
Triple Negative Breast Neoplasms RNA, Long Noncoding Neoplasm Proteins Neural Networks, Computer Algorithms Precision Medicine Female Antineoplastic Agents Gene Regulatory Networks RNA, Messenger Gene Expression Regulation, Neoplastic Humans
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Bioinformatics and machine learning methodologies to identify the effects of central nervous system disorders on glioblastoma progression.

Briefings in bioinformatics Sep 2, 2021
Glioblastoma (GBM) is a common malignant brain tumor which often presents as a comorbidity with central nervous system (CNS) disorders. Both CNS disorders and GBM cells release glutamate and show an abnormality, but differ in cellular behavior. So, t...
Humans Machine Learning Brain Neoplasms Gene Expression Profiling Neoplasm Proteins Glioblastoma Datasets as Topic Central Nervous System Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic Signal Transduction Gene Ontology Atlases as Topic Glutamic Acid Proportional Hazards Models Kaplan-Meier Estimate Molecular Sequence Annotation
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Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma.

Briefings in bioinformatics Jul 20, 2021
Uveal melanoma (UVM) is the most common primary intraocular human malignancy with a high mortality rate. Aberrant DNA methylation has rapidly emerged as a diagnostic and prognostic signature in many cancers. However, such DNA methylation signature av...
Transcriptome Gene Expression Regulation, Neoplastic DNA Methylation Neoplasm Proteins Predictive Value of Tests Disease-Free Survival DNA, Neoplasm Uveal Neoplasms Survival Rate Male Middle Aged Gene Expression Profiling Aged Aged, 80 and over Adult Uveal Melanoma Humans Machine Learning Female Melanoma
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Identification of pan-cancer Ras pathway activation with deep learning.

Briefings in bioinformatics Jul 20, 2021
The identification of hidden responders is often an essential challenge in precision oncology. A recent attempt based on machine learning has been proposed for classifying aberrant pathway activity from multiomic cancer data. However, we note several...
Mutation Programming Languages Gene Dosage ras Proteins Deep Learning RNA-Seq Signal Transduction Neoplasm Proteins Humans Neoplasms
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DeepHPV: a deep learning model to predict human papillomavirus integration sites.

Briefings in bioinformatics Jul 20, 2021
Human papillomavirus (HPV) integrating into human genome is the main cause of cervical carcinogenesis. HPV integration selection preference shows strong dependence on local genomic environment. Due to this theory, it is possible to predict HPV integr...
Viral Proteins Alphapapillomavirus Virus Integration Papillomavirus Infections Models, Genetic Neoplasm Proteins Humans Female Uterine Cervical Neoplasms Deep Learning
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Identification of Cancer Biomarkers in Human Body Fluids by Using Enhanced Physicochemical-incorporated Evolutionary Conservation Scheme.

Current topics in medicinal chemistry Jan 1, 2020
OBJECTIVE: Cancer is one of the most serious diseases affecting human health. Among all current cancer treatments, early diagnosis and control significantly help increase the chances of cure. Detecting cancer biomarkers in body fluids now is attracti...
Biomarkers, Tumor Neoplasms Support Vector Machine Databases, Protein Humans Neoplasm Proteins Body Fluids Chemistry, Physical Position-Specific Scoring Matrices
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