AIMC Topic: DNA Copy Number Variations
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Utilization of circulating cell-free DNA profiling to guide first-line chemotherapy in advanced lung squamous cell carcinoma.
Theranostics
Jan 1, 2021
Platinum-based chemotherapy is one of treatment mainstay for patients with advanced lung squamous cell carcinoma (LUSC) but it is still a "one-size fits all" approach. Here, we aimed to investigate the predictive and monitoring role of circulating c...
Lung Neoplasms
Antineoplastic Combined Chemotherapy Protocols
Treatment Outcome
Cell-Free Nucleic Acids
Survival Rate
Male
Middle Aged
Humans
Progression-Free Survival
Machine Learning
Deoxycytidine
Carcinoma, Squamous Cell
Gemcitabine
DNA Copy Number Variations
Aged
Circulating Tumor DNA
Prognosis
Cisplatin
Female
Paclitaxel
REDBot: Natural language process methods for clinical copy number variation reporting in prenatal and products of conception diagnosis.
Molecular genetics & genomic medicine
Sep 22, 2020
BACKGROUND: Current copy number variation (CNV) identification methods have rapidly become mature. However, the postdetection processes such as variant interpretation or reporting are inefficient. To overcome this situation, we developed REDBot as an...
Deep learning based feature-level integration of multi-omics data for breast cancer patients survival analysis.
BMC medical informatics and decision making
Sep 15, 2020
BACKGROUND: Breast cancer is the most prevalent and among the most deadly cancers in females. Patients with breast cancer have highly variable survival lengths, indicating a need to identify prognostic biomarkers for personalized diagnosis and treatm...
A machine learning framework for genotyping the structural variations with copy number variant.
BMC medical genomics
Aug 27, 2020
BACKGROUND: Genotyping of structural variation is an important computational problem in next generation sequence data analysis. However, in cancer genomes, the copy number variant(CNV) often coexists with other types of structural variations which si...
Integrating multi-omics data by learning modality invariant representations for improved prediction of overall survival of cancer.
Methods (San Diego, Calif.)
Aug 5, 2020
Breast and ovarian cancers are the second and the fifth leading causes of cancer death among women. Predicting the overall survival of breast and ovarian cancer patients can facilitate the therapeutics evaluation and treatment decision making. Multi-...
Classifying Breast Cancer Subtypes Using Deep Neural Networks Based on Multi-Omics Data.
Genes
Aug 4, 2020
With the high prevalence of breast cancer, it is urgent to find out the intrinsic difference between various subtypes, so as to infer the underlying mechanisms. Given the available multi-omics data, their proper integration can improve the accuracy o...
Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration.
Genomics
Mar 29, 2020
Gene expression analysis plays a significant role for providing molecular insights in cancer. Various genetic and epigenetic factors (being dealt under multi-omics) affect gene expression giving rise to cancer phenotypes. A recent growth in understan...
Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.
Clinical cancer research : an official journal of the American Association for Cancer Research
Jan 7, 2020
PURPOSE: Tumor genomic features have been of particular interest because of their potential impact on the tumor immune microenvironment and response to immunotherapy. Due to the substantial heterogeneity, an integrative approach incorporating diverse...
Evaluation of colorectal cancer subtypes and cell lines using deep learning.
Life science alliance
Dec 2, 2019
Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cel...
A Deep Learning Approach for Detecting Copy Number Variation in Next-Generation Sequencing Data.
G3 (Bethesda, Md.)
Nov 5, 2019
Copy number variants (CNV) are associated with phenotypic variation in several species. However, properly detecting changes in copy numbers of sequences remains a difficult problem, especially in lower quality or lower coverage next-generation sequen...
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