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Neoplasm Proteins

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DriverML: a machine learning algorithm for identifying driver genes in cancer sequencing studies.

Nucleic acids research
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...

A parsimonious 3-gene signature predicts clinical outcomes in an acute myeloid leukemia multicohort study.

Blood advances
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...

Deep learning for tumor classification in imaging mass spectrometry.

Bioinformatics (Oxford, England)
MOTIVATION: Tumor classification using imaging mass spectrometry (IMS) data has a high potential for future applications in pathology. Due to the complexity and size of the data, automated feature extraction and classification steps are required to f...

The co-regulators SRC-1 and SMRT are involved in interleukin-6-induced androgen receptor activation.

European cytokine network
BACKGROUND: The androgen receptor (AR) can be stimulated by interleukin-6 (IL-6) in the absence of androgens to induce prostate cancer progression. The purpose of this study was to investigate whether the co-activator steroid receptor coactivator-1 (...

Protein interaction network constructing based on text mining and reinforcement learning with application to prostate cancer.

IET systems biology
Constructing interaction network from biomedical texts is a very important and interesting work. The authors take advantage of text mining and reinforcement learning approaches to establish protein interaction network. Considering the high computatio...

Regularised extreme learning machine with misclassification cost and rejection cost for gene expression data classification.

International journal of data mining and bioinformatics
The main purpose of traditional classification algorithms on bioinformatics application is to acquire better classification accuracy. However, these algorithms cannot meet the requirement that minimises the average misclassification cost. In this pap...

A hybrid ensemble method based on double disturbance for classifying microarray data.

Bio-medical materials and engineering
Microarray data has small samples and high dimension, and it contains a significant amount of irrelevant and redundant genes. This paper proposes a hybrid ensemble method based on double disturbance to improve classification performance. Firstly, ori...

Classification of Breast Cancer Resistant Protein (BCRP) Inhibitors and Non-Inhibitors Using Machine Learning Approaches.

Combinatorial chemistry & high throughput screening
The breast cancer resistant protein (BCRP) is an important transporter and its inhibitors play an important role in cancer treatment by improving the oral bioavailability as well as blood brain barrier (BBB) permeability of anticancer drugs. In this ...