Journal of Clinical Bioinformatics

BACKGROUND: Identification of prognostic mRNA biomarkers has been done for various cancer types. The data that are published from such studies are archived in public repositories. There are hundreds of such datasets available for multiple cancer types in public repositories. Wealth of such data can be utilized to study prognostic implications of mRNA in different cancers as well as in different populations or subtypes of same cancer. DESCRIPTION: We have created a web application that can be used for studying prognostic implications of mRNA biomarkers in a variety of cancers...

BACKGROUND: The ciliary body epithelia (CBE) of the eye produce the aqueous humor (AH). The equilibrium between the AH production by the CBE and the outflow through the trabecular meshwork, ultimately determines the intraocular pressure (IOP). An increased IOP is a major risk factor for primary open angle glaucoma (POAG). This study aims to elucidate the molecular machinery of the most important function of the CBE: the AH production and composition, and to find possible new molecular clues for POAG and AH production-lowering drugs...

BACKGROUND: The continuing discovery of new types and functions of small non-coding RNAs is suggesting the presence of regulatory mechanisms far more complex than the ones currently used to study and design Gene Regulatory Networks. Just focusing on the roles of micro RNAs (miRNAs), they have been found to be part of several intra-pathway regulatory motifs. However, inter-pathway regulatory mechanisms have been often neglected and require further investigation. RESULTS: In this paper we present the result of a systems biology study aimed at analyzing a high-level inter-pathway regulatory motif called Pathway Protection Loop, not previously described, in which miRNAs seem to play a crucial role in the successful behavior and activation of a pathway...

BACKGROUND: Large scale understanding of complex and dynamic alterations in cellular and subcellular levels during cancer in contrast to normal condition has facilitated the emergence of sophisticated systemic approaches like network biology in recent times. As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e...

MicroRNAs (miRNAs) are remarkable molecules that appear to have a fundamental role in the biology of the cell. They constitute a class of non-protein encoding RNA molecules which have now emerged as key players in regulating the activity of mRNA. miRNAs are small RNAmolecules around 22 nucleotides in length, which affect the activity of specific mRNA, directly degrading it and/or preventing its translation into protein. The science of miRNAs holds them as candidate biomarkers for the early detection and management of cancer...

UNLABELLED: BACKGROUND: Mass spectrometry is an important analytical tool for clinical proteomics. Primarily employed for biomarker discovery, it is increasingly used for developing methods which may help to provide unambiguous diagnosis of biological samples. In this context, we investigated the classification of phenotypes by applying support vector machine (SVM) on experimental data obtained by MudPIT approach. In particular, we compared the performance capabilities of SVM by using two independent collection of complex samples and different data-types, such as mass spectra (m/z), peptides and proteins...

BACKGROUND: EHR (Electronic Health Record) system has led to development of specialized form of clinical databases which enable storage of information in temporal prospective. It has been a big challenge for mining this form of clinical data considering varied temporal points. This study proposes a conjoined solution to analyze the clinical parameters akin to a disease. We have used "association rule mining algorithm" to discover association rules among clinical parameters that can be augmented with the disease...

BACKGROUND: Detection of brain lesions disseminated in space and time by magnetic resonance imaging remains a cornerstone for the diagnosis of clinically definite multiple sclerosis. We have sought to determine if gene expression biomarkers could contribute to the clinical diagnosis of multiple sclerosis. METHODS: We employed expression levels of 30 genes in blood from 199 subjects with multiple sclerosis, 203 subjects with other neurologic disorders, and 114 healthy control subjects to train ratioscore and support vector machine algorithms...

The microRNA miR-155 is prominent in cancer biology. Among microRNAs that have been linked to cancer, it is the most commonly overexpressed in malignancies (PNAS 109:20047-20052, 2012). Since its discovery, miR-155 has been implicated in promoting cancers of the breast, lung, liver, and lymphatic system. As such, targeted therapies may prove beneficial to cancer treatment. This review discusses the important role of miR-155 in oncogenesis. It synthesizes information from ten recent papers on miR-155, and includes an analysis and discussion of its association with cancer, interactions with other miRNAs, mechanisms of action, and the most promising available treatment options...

Asthma is a prevalent disease in pediatric patients and most of the cases begin at very early years of life in children. Early identification of patients at high risk of developing the disease can alert us to provide them the best treatment to manage asthma symptoms. Often evaluating patients with high risk of developing asthma from huge data sets (e.g., electronic medical record) is challenging and very time consuming, and lack of complex analysis of data or proper clinical logic determination might produce invalid results and irrelevant treatments...

BACKGROUND: Immunoglobulin (that is, antibody) and T cell receptor genes are created through somatic gene rearrangement from gene segment libraries. Immunoglobulin genes are further diversified by somatic hypermutation and selection during the immune response. Studying the repertoires of these genes yields valuable insights into immune system function in infections, aging, autoimmune diseases and cancers. The introduction of high throughput sequencing has generated unprecedented amounts of repertoire and mutation data from immunoglobulin genes...

BACKGROUND: Next-generation sequencing has enabled examination of variation at the DNA sequence level and can be further enhanced by evaluation of the variants at the protein level. One powerful method is to visualize these data often revealing patterns not immediately apparent in a text version of the same data. Many investigators are interested in knowing where their amino acid changes reside within a protein. Clustering of variation within a protein versus non-clustering can show interesting aspects of the biological changes happening in disease...

BACKGROUND: Quantification and normalization of RT-qPCR data critically depends on the expression of so called reference genes. Our goal was to develop a strategy for the selection of reference genes that utilizes microarray data analysis and combines known approaches for gene stability evaluation and to select a set of appropriate reference genes for research and clinical analysis of breast samples with different receptor and cancer status using this strategy. METHODS: A preliminary search of reference genes was based on high-throughput analysis of microarray datasets...

BACKGROUND: DNA copy number variations (CNV) constitute an important source of genetic variability. The standard method used for CNV detection is array comparative genomic hybridization (aCGH). RESULTS: We propose a novel multiple sample aCGH analysis methodology aiming in rare CNVs detection. In contrast to the majority of previous approaches, which deal with cancer datasets, we focus on constitutional genomic abnormalities identified in a diverse spectrum of diseases in human...

BACKGROUND: Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. RESULTS: We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA)...

BACKGROUND: Whole genome microarray gene expression profiling is the 'gold standard' for the discovery of prognostic and predictive genetic markers for human cancers. However, suitable research material is lacking as most diagnostic samples are preserved as formalin-fixed, paraffin-embedded tissue (FFPET). We tested a new workflow and data analysis method optimized for use with FFPET samples. METHODS: Sixteen breast tumor samples were split into matched pairs and preserved as FFPET or fresh-frozen (FF)...

BACKGROUND: Like all other neurodegenerative diseases, Alzheimer's disease (AD) remains a very challenging and difficult problem for diagnosis and therapy. For many years, only historical, behavioral and psychiatric measures have been available to AD cases. Recently, a definitive diagnostic framework, using biomarkers and imaging, has been proposed. In this paper, we propose a promising diagnostic methodology for the framework. METHODS: In a previous paper, we developed an efficient SVM (Support Vector Machine) based method, which we have now applied to discover important biomarkers and target networks which provide strategies for AD therapy...

BACKGROUND: Exploring stromal changes associated with tumor growth and development is a growing area of oncologic research. In order to study molecular changes in the stroma it is recommended to separate tumor tissue from stromal tissue. This is relevant to xenograft models where tumors can be small and difficult to separate from host tissue. We introduce a novel definition of cross-alignment/cross-hybridization to compare qualitatively the ability of high-throughput mRNA sequencing, RNA-Seq, and microarrays to detect tumor and stromal expression from mixed 'pseudo-xenograft' samples vis-à-vis genes and pathways in cross-alignment (RNA-Seq) and cross-hybridization (microarrays)...

BACKGROUND: MicroRNAs were found to play an important role in cancers and several literatures exist to describe the relationship between microRNA and cancer, but the expression pattern was still faintly. There is a need for a comprehensive collection and summary of the interactions under experimental support. DESCRIPTION: TUMIR (https://www.ncrnalab.com/TUMIR/), a manually extracted database of experimentally supported microRNA-cancer relationship, aims at providing a large, high-quality, validated comprehensive resource of microRNA deregulation in various cancers...

BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes derived from distinct pathways are associated with a breast cancer risk. Identifying possible SNP-SNP interactions in genome-wide case-control studies is an important task when investigating genetic factors that influence common complex traits; the effects of SNP-SNP interaction need to be characterized. Furthermore, observations of the complex interplay (interactions) between SNPs for high-dimensional combinations are still computationally and methodologically challenging...