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Gene Expression Regulation, Neoplastic

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Effects of Jiazhu decoction in combination with cyclophosphamide on breast cancer in mice.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan Oct 1, 2019
OBJECTIVE: To investigate the therapeutic effects of Jiazhu decoction (JZD) in combination with cyclophosphamide (CTX) on the growth of breast cancer in mice and to explore the possible molecular mechanisms of action.
Drug Interactions Breast Neoplasms Xenograft Model Antitumor Assays Animals Cyclin D1 beta Catenin Antineoplastic Agents RNA, Messenger Cyclophosphamide Cell Line, Tumor Gene Expression Regulation, Neoplastic Mice Genes, myc Cell Proliferation Drugs, Chinese Herbal
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Artificial intelligence in drug combination therapy.

Briefings in bioinformatics Jul 19, 2019
Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many cases, one drug cannot target all necessary points of intervention. For example, in cancer therapy, a...
Artificial Intelligence Machine Learning Neoplasms Deep Learning Computational Biology Humans Neural Networks, Computer Drug Interactions Expert Systems Drug Therapy, Combination Drug Resistance Stochastic Processes Logistic Models Gene Expression Regulation, Neoplastic Support Vector Machine Bayes Theorem Least-Squares Analysis
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SuperCT: a supervised-learning framework for enhanced characterization of single-cell transcriptomic profiles.

Nucleic acids research May 7, 2019
Characterization of individual cell types is fundamental to the study of multicellular samples. Single-cell RNAseq techniques, which allow high-throughput expression profiling of individual cells, have significantly advanced our ability of this task....
Humans Software Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Cluster Analysis Pancreatic Neoplasms Supervised Machine Learning Animals Gene Expression Profiling Transcriptome Single-Cell Analysis Mice High-Throughput Nucleotide Sequencing Datasets as Topic Cell Lineage RNA, Small Cytoplasmic
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DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Nucleic acids research May 7, 2019
Although rapid progress has been made in computational approaches for prioritizing cancer driver genes, research is far from achieving the ultimate goal of discovering a complete catalog of genes truly associated with cancer. Driver gene lists predic...
Atlases as Topic Oncogenes Gene Expression Regulation, Neoplastic Cell Proliferation Nuclear Proteins Cell Movement Humans Neoplasm Proteins Machine Learning Mutation Software Datasets as Topic Neoplasms Monte Carlo Method Cell Line, Tumor Cell Cycle Proteins
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A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study.

Blood advances Apr 23, 2019
Acute myeloid leukemia (AML) is a genetically heterogeneous hematological malignancy with variable responses to chemotherapy. Although recurring cytogenetic abnormalities and gene mutations are important predictors of outcome, 50% to 70% of AMLs harb...
Predictive Value of Tests Models, Biological Disease-Free Survival Child Gene Expression Regulation, Neoplastic Databases, Genetic Neoplasm Proteins Adult Survival Rate Leukemia, Myeloid, Acute Male Middle Aged Risk Assessment Infant Adolescent Child, Preschool Humans Neural Networks, Computer Female Infant, Newborn
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[Effects of long non-coding RNA RP1-90L14.1 on the biological behaviors of cancer prostate LNCaP cells and its regulating mechanisms].

Zhonghua nan ke xue = National journal of andrology Mar 1, 2019
OBJECTIVE: To investigate the effects of long non-coding RNA RP1-90L14.1 on the proliferation, migration and invasion of prostate cancer LNCaP cells and the expressions of GRIN2A and BACE2.
Transfection Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases Receptors, N-Methyl-D-Aspartate Cell Proliferation Humans Male Cell Movement Cell Line, Tumor Neoplasm Invasiveness Gene Expression Regulation, Neoplastic RNA, Long Noncoding Prostatic Neoplasms
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Exploring microRNA Regulation of Cancer with Context-Aware Deep Cancer Classifier.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
BACKGROUND: MicroRNAs (miRNAs) are small, non-coding RNA that regulate gene expression through post-transcriptional silencing. Differential expression observed in miRNAs, combined with advancements in deep learning (DL), have the potential to improve...
Humans Neural Networks, Computer Female Male Computational Biology Molecular Sequence Annotation Neoplasms Sequence Analysis, RNA Gene Ontology Gene Expression Regulation, Neoplastic Gene Expression Profiling Databases, Nucleic Acid MicroRNAs Diagnosis, Computer-Assisted High-Throughput Nucleotide Sequencing Deep Learning
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Constructing a Risk Prediction Model for Lung Cancer Recurrence by Using Gene Function Clustering and Machine Learning.

Combinatorial chemistry & high throughput screening Jan 1, 2019
OBJECTIVE: A significant proportion of patients with early non-small cell lung cancer (NSCLC) can be cured by surgery. The distant metastasis of tumors is the most common cause of treatment failure. Precisely predicting the likelihood that a patient ...
Recurrence Gene Expression Regulation, Neoplastic Carcinoma, Non-Small-Cell Lung Models, Biological Multigene Family Humans Machine Learning Female Risk Factors Male Middle Aged Lung Neoplasms
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Feature specific quantile normalization enables cross-platform classification of molecular subtypes using gene expression data.

Bioinformatics (Oxford, England) Jun 1, 2018
MOTIVATION: Molecular subtypes of cancers and autoimmune disease, defined by transcriptomic profiling, have provided insight into disease pathogenesis, molecular heterogeneity and therapeutic responses. However, technical biases inherent to different...
Sequence Analysis, RNA Gene Expression Regulation, Neoplastic Female Support Vector Machine Colonic Neoplasms Humans Software Oligonucleotide Array Sequence Analysis Colorectal Neoplasms Breast Neoplasms Neoplasms Gene Expression Profiling
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DeepSynergy: predicting anti-cancer drug synergy with Deep Learning.

Bioinformatics (Oxford, England) May 1, 2018
MOTIVATION: While drug combination therapies are a well-established concept in cancer treatment, identifying novel synergistic combinations is challenging due to the size of combinatorial space. However, computational approaches have emerged as a tim...
Antineoplastic Combined Chemotherapy Protocols Support Vector Machine Gene Expression Profiling Humans Deep Learning Software Cell Line, Tumor Neoplasms Computational Biology Gene Expression Regulation, Neoplastic
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