Comparative Statistic Module(CSM) provides more reliable list of significant genes to genomics researchers by offering the commonly selected genes and a method of choice by calculating the rank of each statistical test based on the average ranking of common genes across the five statistical methods, i.e. t-test, Kruskal-Wallis (Wilcoxon signed rank) test, SAM, two sample multiple test, and Empirical Bayesian test. This statistical analysis module is implemented in Perl, and R languages.
Genomics

This article is a mini-review that provides a general overview for next-generation sequencing (NGS) and introduces one of the most popular NGS applications, whole genome sequencing (WGS), developed from the expansion of human genomics. NGS technology has brought massively high throughput sequencing data to bear on research questions, enabling a new era of genomic research. Development of bioinformatic software for NGS has provided more opportunities for researchers to use various applications in genomic fields. De novo genome assembly and large scale DNA resequencing to understand genomic variations are popular genomic research tools for processing a tremendous amount of data at low cost. Studies on transcriptomes are now available, from previous-hybridization based microarray methods. Epigenetic studies are also available with NGS applications such as whole genome methylation sequencing and chromatin immunoprecipitation followed by sequencing. Human genetics has faced a new paradigm of research and medical genomics by sequencing technologies since the Human Genome Project. The trend of NGS technologies in human genomics has brought a new era of WGS by enabling the building of human genomes databases and providing appropriate human reference genomes, which is a necessary component of personalized medicine and precision medicine.
Chromatin Immunoprecipitation ; Computational Biology ; DNA ; Epigenomics ; Genetics, Medical ; Genome* ; Genome, Human ; Genomics ; High-Throughput Nucleotide Sequencing ; Human Genome Project ; Humans ; Methylation ; Precision Medicine ; Sequence Analysis, RNA ; Transcriptome

The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced.
Complement System Proteins ; Genome ; Genomics ; Glycomics ; Mass Spectrometry ; Metabolism ; Metabolome ; Metabolomics* ; Phenotype ; Proteome ; Proteomics ; Transcriptome

Nutritional genomics (nutrigenomics) is the application of high-throughput functional genomics technologies to nutritional science lying in the interface between the nutritional environment and genetic process. It seeks to provide a molecular genetic understanding of how common dietary nutrition affects health by altering the expression or structure of an individual's genetic makeup. On the other hand, nutrigenetics is significantly different from nutrigenomics since nutrigenetics has been used for decades in certain rare monogenic diseases such as phenylketonuria, and has the potential to provide a basis for personalized dietary recommendation based on the individual's specific genetic background in order to prevent common multifactorial disorders decades before their clinical manifestation. The human genome maps and SNP databases, together with the rapid development of tools suitable for investigating genetic and epigenetic changes in small tissue biopsies provide the means to begin the test hypothesis about the mechanisms by which diet influences disease risk including cancer directly in human subjects, could be inevitable flatforms for clinical application to achieve targeted therapy in near future.
Biopsy ; Deception ; Diet ; Epigenomics ; Genetic Processes ; Genome ; Genome, Human ; Genomics ; Hand ; Humans ; Molecular Biology ; Nutrigenomics ; Nutritional Sciences ; Phenylketonurias

Because autoimmune diseases (AIDs) result from a complex combination of genetic and epigenetic factors, as well as an altered immune response to endogenous or exogenous antigens, systems biology approaches have been widely applied. The use of multi-omics approaches, including blood transcriptomics, genomics, epigenetics, proteomics, and metabolomics, not only allow for the discovery of a number of biomarkers but also will provide new directions for further translational AIDs applications. Systems biology approaches rely on high-throughput techniques with data analysis platforms that leverage the assessment of genes, proteins, metabolites, and network analysis of complex biologic or pathways implicated in specific AID conditions. To facilitate the discovery of validated and qualified biomarkers, better-coordinated multi-omics approaches and standardized translational research, in combination with the skills of biologists, clinicians, engineers, and bioinformaticians, are required.
Autoimmune Diseases* ; Biomarkers ; Epigenomics ; Genomics ; Metabolomics ; Proteomics ; Statistics as Topic ; Systems Biology* ; Translational Medical Research

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic, proteomic and postgenomic data means that many of the challenges in biomedical research are now challenges in informatics. Clinical informatics has long developed technologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. Biomedical informatics, powered by high throughput technologies, genomic-scale databases, and advanced clinical information system, is likely to transform our biomedical understanding forever much the same way that biochemistry did to biology a generation ago. The emergence of health and biomedical informatics revolutionizing both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics.
Biochemistry ; Biology ; Computational Biology ; Gene Expression ; Genomics ; Human Genome Project ; Informatics* ; Information Systems ; Medical Informatics ; Oligonucleotide Array Sequence Analysis

Bioinformatics is a rapidly emerging field of biomedical research. A flood of large-scale genomic, proteomic and postgenomic data means that many of the challenges in biomedical research are now challenges in informatics. Clinical informatics has long developed technologies to improve biomedical research and clinical care by integrating experimental and clinical information systems. Biomedical informatics, powered by high throughput technologies, genomic-scale databases, and advanced clinical information system, is likely to transform our biomedical understanding forever much the same way that biochemistry did to biology a generation ago. The emergence of health and biomedical informatics revolutionizing both bioinformatics and clinical informatics will eventually change the current practice of medicine, including diagnostics, therapeutics, and prognostics.
Biochemistry ; Biology ; Computational Biology ; Gene Expression ; Genomics ; Human Genome Project ; Informatics* ; Information Systems ; Medical Informatics ; Oligonucleotide Array Sequence Analysis

Stem cell research has been widely studied over the last few years and has attracted increasing attention from researchers in all fields of medicine due to its potential to treat many previously incurable diseases by replacing damaged cells or tissues. As illustrated by hematopoietic stem research, understanding stem cell differentiation at molecular levels is essential for both basic research and for clinical applications of stem cells. Although multiple integrative analyses, such as genomics, epigenomics, transcriptomics and proteomics, are required to understand stem cell biology, proteomics has a unique position in stem cell research. For example, several major breakthroughs in HSC research were due to the identification of proteins such as colony-stimulating factors (CSFs) and cell-surface CD molecules. In 2007, the Human Proteome Organization (HUPO) and the International Society for Stem Cell Research (ISSCR) launched the joint Proteome Biology of Stem Cells Initiative. A systematic proteomics approach to understanding stem cell differentiation will shed new light on stem cell biology and accelerate clinical applications of stem cells.
Biology ; Colony-Stimulating Factors ; Epigenomics ; Genomics ; Humans ; Joints ; Light ; Proteins ; Proteome ; Proteomics ; Stem Cell Research ; Stem Cells

Bioinformatics is the information technology to deal with biological data. Recently emerging systems biology has drawn great interest inspired by world-wide efforts for modeling and analyzing biological processes with a systems perspective. Bioinformatics, which has analyzed multi-omics data such as genomics, transcriptomics, and proteomics, and explored novel biological patterns embedded within the data, now has a transition to its application to systems biology, called systems bioinformatics. Systems bioinformatics includes various research areas: system modeling, system structure and dynamics analysis, causality analysis, and multi-omics data fusion. In this review, we introduce bioinformatics for genomics, transcriptomics, proteomics, and systems biology according to the different aspects of biological processes.
Biological Processes ; Computational Biology ; Genomics ; Proteomics ; Systems Biology

Recent rapid advances in genetic research are ushering us into the genome sequence era, where an individual's genome information is utilized for clinical practice. The most spectacular results of the human genome study have been provided by genome-wide association studies (GWASs). This is a review of the history of GWASs as related to my work. Further efforts are necessary to make full use of its potential power to medicine.
Genetic Research ; Genome ; Genome, Human ; Genome-Wide Association Study ; HapMap Project ; Human Genome Project ; Humans