understanding the genetic regulatory networks, the discovery of interactions between genes, and understanding regulatory processes in a cell at the gene level, is one of the major goals of system biology and computational biology. modeling gene regulatory networks, describing the actions of the cells at the molecular level and is used in medicine and molecular biology applications such as metab...

Breast cancer (BC) remains the most dominant among women worldwide. Numerous BC gene expression microarray-based studies have been employed in classification and prognosis. The availability of microarray data together with advanced methods has enabled accurate precise classification. Nevertheless, datasets suffer from a large number levels, limited sample size, irrelevant features. Additionally...

Background: LncRNA GHRLOS is a long non-coding RNAs (lncRNAs). Microarray detection for expression profile revealed that lncRNA was significantly under-expressed in colon cancer tissues, while its role tumor remained unclear.

MicroRNAs (miRNAs) are a functional small non-coding RNA and play essential roles in gene regulation indevelopment, differentiation proliferation. In order to investigate the miRNAs function Lewis rat hippocampal development, this study, newborn adult hippocampi were deliberately selected analyze miRNA expression profiles by microarray. Microarray analyses identified 22 differentially expressed...

Microarray techniques are widely employed to monitor the gene expressions that responsible for causing cancer. Freely available microarray lymphoma dataset encompassing 7,129 features with 58 samples in Diffuse Large B-Cell Lymphoma (DLBCL) and 19 Follicular (FL) this research. Feature selection is very crucial classification of cancer high dimension. This paper recommends a structure exploitin...

Salah satu penyakit mematikan penyebab kematian terbesar secara global adalah kanker. Kematian akibat kanker dapat diredam melalui deteksi dini terhadap dengan memanfaatkan teknologi microarray. Namun ini memiliki kekurangan, yaitu jumlah gen (fitur) yang terlalu banyak. Kekurangan tersebut diatasi melakukan seleksi fitur data algoritma digunakan Binary Particle Swarm Optimizationi (BPSO). Pada...

High dimensional microarray datasets are difficult to classify since they have many features with small number ofinstances and imbalanced distribution of classes. This paper proposes a filter-based feature selection method to improvethe classification performance of microarray datasets by selecting the significant features. Combining the concepts ofrough sets, weighted rough set, fuzzy rough se...

 In this paper, we propose a new gene selection algorithm based on Shuffled Frog Leaping Algorithm that is called SFLA-FS. The proposed algorithm is used for improving cancer classification accuracy. Most of the biological datasets such as cancer datasets have a large number of genes and few samples. However, most of these genes are not usable in some tasks for example in cancer classification....