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Over the years, medicine has continuously tried to provide the best treatment for patients. In cancer treatment, science has been at the service of medicine, to treat and discover new and better treatment approaches to “save lives” or increase ...

Cancer is the top cause of death worldwide, and machine learning (ML) has made an indelible mark on the field of early cancer detection, thereby lowering the death toll. ML-based model for cancer diagnosis is done using two forms of data: gene expression ...

Microarrays allow the expression level analysis of thousands of genes simultaneously; thus, it is a common technique used for cancer detection and diagnosis. However, existing microarray datasets have huge data dimension and class imbalance, therefore, ...

Evolutionary and Swarm algorithms show great effectiveness when performing feature selection, classification problems, and other optimization tasks. These scenarios highlight several algorithms such as Genetic Algorithm, Particle Swarm Optimization, ...

Our aim was to make comprehensive analyses of mRNAs and miRNAs in early diagnosis of Colorectal Cancer (CRC) via Principal Component Analysis (PCA)-based Unsupervised Feature Extraction (UFE) and additional bioinformatics approaches. miRNA and mRNA ...

The paper proposes a novel approach for image segmentation in case of bio-medical applications. The medical images considered for our analysis are drawn from microarray image databases and they are generally used for the estimation of gene ...

Breast cancer is one of the most malignant cancers in women worldwide. The aim of the present study was to explore the underlying biological mechanisms of breast cancer. For this purpose, we propose a novel framework to reveal mechanisms that drive ...

High Dimensional cancer microarray is devilishly challenging while finding the best features for classification. In this paper a new algorithm is proposed based on iterative qualitative mutual information to choose the features that can provide optimal ...

Research has proved that DNA Microarray data containing gene expression profiles are potentially excellent diagnostic tools in the medical industry. A persistent problem with regard to accessible microarray datasets is that the number of samples are much ...

Accurate reconstruction of gene regulatory networks from time-series gene expression data is a significant challenge for computer scientists. In this paper, we have proposed a genetic algorithm and flower pollination algorithm hybrid for the reverse ...

Primary skin cancer can be divided into basal cell carcinoma(BCC), squamous cell carcinoma and melanoma three types. Especially, BCC incidence is as high as 80% with 10% global incidence increasing each year. Although BCC has low metastatic and lower ...

We present a method to visualize gene co-expression from microarray data by plotting profiles of dissimilarity within gene-sets of biological pathways. A gene co-expression network is created by computing the correlation between each gene pair in a gene-...

Cancer is one of main non-communicable diseases. Acute Lymphoblastic Leukemia (ALL), a type of white blood cancer, is one of the most common pediatric cancers. Analysis of cancer prognosis is necessary to determine the proper treatment for each patient. ...

There is a cultural divide between computer scientists and biologists that needs to be addressed. The two disciplines used to be quite unrelated but many new research areas have arisen from their synergy. We selectively review two multi-disciplinary ...

Microarray is a common technique used to identify differentially expressed genes for a target concept. The output is demonstrated in a heatmap, and biologists analyze related terms of gene ontology to identify characteristics of differentially expressed ...

Microarray technology can be used as an efficient diagnostic system to recognise diseases such as tumours or to discriminate between different types of cancers in normal tissues. This technology has received increasing attention from the bioinformatics ...

Profiling cancer molecules has several advantages; however, using microarray technology in routine clinical diagnostics is challenging for physicians. The classification of microarray data has two main limitations: 1) the data set is unreliable for ...

A hybrid framework composed of two stages for gene selection and classification of DNA microarray data is proposed. At the first stage, five traditional statistical methods are combined for preliminary gene selection (Multiple Fusion Filter). Then, ...

Using microarray techniques, it is possible to measure the expression levels of thousands of genes under several experimental conditions. Extracting information from microarray data is an important problem in Bioinformatics scope. Producing overlapping ...

Increased understanding of the transcriptomic patterns underlying head and neck squamous cell carcinoma (HNSCC) can facilitate earlier diagnosis and better treatment outcomes. Integrating knowledge from multiple studies is necessary to identify ...