Articles
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Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S21
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p-BioSPRE - p-medicine Biospecimen Search and Project Request Engine
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S20 -
BBMRI catalogue
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S19 -
XNAT imaging platform for BioMedBridges and CTMM TraIT
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S18 -
TRANSFoRm eCRF
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S17 -
TRANSFoRm Query Workbench
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S16 -
TRANSFoRm Data quality tool
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S15 -
Mobile eHealth solution (ePRO)
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S14 -
EHR4CR central workbench
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S13 -
EHR4CR local workbench
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S12 -
Decima
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S11 -
Recruitment and feasibility tool
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S10 -
tranSMART
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S9 -
MOLGENIS catalogue
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S8 -
Clinical trials information mediator (CTIM)
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S7 -
The Integrated Data Repository Toolkit (IDRT): accelerating translational research infrastructures
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S6 -
MOLGENIS/OMX for multi-omics and personalized medicine
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S5 -
VISTA Trials
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S4 -
ObTiMA
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S3 -
OpenClinica
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S2 -
First Clinical Research Informatics (CRI) Solutions Day: advanced IT support from EU projects for clinical trials
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):A1 -
Clinical research informatics (CRI): overview over new tools and services
Citation: Journal of Clinical Bioinformatics 2015 5(Suppl 1):S1 -
Comparative efficacy and acceptability of five anti-tubercular drugs in treatment of multidrug resistant tuberculosis: a network meta-analysis
Multidrug resistant tuberculosis (MDR-TB) is a serious form of tuberculosis (TB). There is no recognized effective treatment for MDR-TB, although there are a number of publications that have reported positive ...
Citation: Journal of Clinical Bioinformatics 2015 5:5 -
Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine
As research laboratories and clinics collaborate to achieve precision medicine, both communities are required to understand mandated electronic health/medical record (EHR/EMR) initiatives that will be fully im...
Citation: Journal of Clinical Bioinformatics 2015 5:4 -
Metabolomics and partial least square discriminant analysis to predict history of myocardial infarction of self-claimed healthy subjects: validity and feasibility for clinical practice
The dynamics of metabolomics in establishing a prediction model using partial least square discriminant analysis have enabled better disease diagnosis; with emphasis on early detection of diseases. We attempte...
Citation: Journal of Clinical Bioinformatics 2015 5:3 -
Variations in genome-wide RNAi screens: lessons from influenza research
Genome-wide RNA interference (RNAi) screening is an emerging and powerful technique for genetic screens, which can be divided into arrayed RNAi screen and pooled RNAi screen/selection based on different screen...
Citation: Journal of Clinical Bioinformatics 2015 5:2 -
K-core decomposition of a protein domain co-occurrence network reveals lower cancer mutation rates for interior cores
Network biology currently focuses primarily on metabolic pathways, gene regulatory, and protein-protein interaction networks. While these approaches have yielded critical information, alternative methods to ne...
Citation: Journal of Clinical Bioinformatics 2015 5:1 -
Copy number variation analysis based on AluScan sequences
AluScan combines inter-Alu PCR using multiple Alu-based primers with opposite orientations and next-generation sequencing to capture a huge number of Alu-proximal genomic sequences for investigation. Its requirem...
Citation: Journal of Clinical Bioinformatics 2014 4:15 -
Analysis for co-occurring sequence features identifies link between common synonymous variant and an early-terminated NPC1 isoform
Direct assessment of allelic phase for DNA and RNA features of diploid genomes has been challenging for Sanger sequencing, due to its allele-conflating base-calling signal. Massively parallel sequencing techno...
Citation: Journal of Clinical Bioinformatics 2014 4:14 -
Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids
Computational methods for mining of biomedical literature can be useful in augmenting manual searches of the literature using keywords for disease-specific biomarker discovery from biofluids. In this work, we ...
Citation: Journal of Clinical Bioinformatics 2014 4:13 -
Extraction of echocardiographic data from the electronic medical record is a rapid and efficient method for study of cardiac structure and function
Measures of cardiac structure and function are important human phenotypes that are associated with a range of clinical outcomes. Studying these traits in large populations can be time consuming and costly. Uti...
Citation: Journal of Clinical Bioinformatics 2014 4:12 -
Meta-analyses of 4 CFTR variants associated with the risk of the congenital bilateral absence of the vas deferens
The aim of our study was to evaluate the relationship between four CFTR variations and the congenital bilateral absence of the vas deferens (CBAVD).
Citation: Journal of Clinical Bioinformatics 2014 4:11 -
Tools to identify linear combination of prognostic factors which maximizes area under receiver operator curve
The linear combination of variables is an attractive method in many medical analyses targeting a score to classify patients. In the case of ROC curves the most popular problem is to identify the linear combina...
Citation: Journal of Clinical Bioinformatics 2014 4:10 -
Interpretation for scales of measurement linking with abstract algebra
The Stevens classification of levels of measurement involves four types of scale: “Nominal”, “Ordinal”, “Interval” and “Ratio”. This classification has been used widely in medical fields and has accomplished a...
Citation: Journal of Clinical Bioinformatics 2014 4:9 -
comoR: a software for disease comorbidity risk assessment
The diagnosis of comorbidities, which refers to the coexistence of different acute and chronic diseases, is difficult due to the modern extreme specialisation of physicians. We envisage that a software dedicat...
Citation: Journal of Clinical Bioinformatics 2014 4:8 -
Estimating age-dependent per-encounter chlamydia trachomatis acquisition risk via a Markov-based state-transition model
Chlamydial infection is a common bacterial sexually transmitted infection worldwide, caused by C. trachomatis. The screening for C. trachomatis has been proven to be successful. However, such success is not fully...
Citation: Journal of Clinical Bioinformatics 2014 4:7 -
A novel tree-based procedure for deciphering the genomic spectrum of clinical disease entities
Dissecting the genomic spectrum of clinical disease entities is a challenging task. Recursive partitioning (or classification trees) methods provide powerful tools for exploring complex interplay among genomic...
Citation: Journal of Clinical Bioinformatics 2014 4:6 -
FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research
A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obta...
Citation: Journal of Clinical Bioinformatics 2014 4:5 -
A novel molecular typing method of Mycobacteria based on DNA barcoding visualization
Different subtypes of Mycobacterium tuberculosis (MTB) may induce diverse severe human infections, and some of their symptoms are similar to other pathogenes, e.g. Nontuberculosis mycobacteria (NTM). So determina...
Citation: Journal of Clinical Bioinformatics 2014 4:4 -
Development of detection method for novel fusion gene using GeneChip exon array
Fusion genes have been recognized to play key roles in oncogenesis. Though, many techniques have been developed for genome-wide analysis of fusion genes, a more efficient method is desired.
Citation: Journal of Clinical Bioinformatics 2014 4:3 -
Combined analysis of chromosomal instabilities and gene expression for colon cancer progression inference
Copy number alterations (CNAs) represent an important component of genetic variations. Such alterations are related with certain type of cancer including those of the pancreas, colon, and breast, among others....
Citation: Journal of Clinical Bioinformatics 2014 4:2 -
Clinical detection of human probiotics and human pathogenic bacteria by using a novel high-throughput platform based on next generation sequencing
The human body plays host to a vast array of bacteria, found in oral cavities, skin, gastrointestinal tract and the vagina. Some bacteria are harmful while others are beneficial to the host. Despite the availa...
Citation: Journal of Clinical Bioinformatics 2014 4:1 -
SN algorithm: analysis of temporal clinical data for mining periodic patterns and impending augury
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 f...
Citation: Journal of Clinical Bioinformatics 2013 3:24 -
Mathematical models for translational and clinical oncology
In the context of translational and clinical oncology, mathematical models can provide novel insights into tumor-related processes and can support clinical oncologists in the design of the treatment regime, do...
Citation: Journal of Clinical Bioinformatics 2013 3:23 -
PROGgene: gene expression based survival analysis web application for multiple cancers
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 avail...
Citation: Journal of Clinical Bioinformatics 2013 3:22 -
In silicoanalysis of the molecular machinery underlying aqueous humor production: potential implications for glaucoma
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 intrao...
Citation: Journal of Clinical Bioinformatics 2013 3:21 -
A systematic analysis of a mi-RNA inter-pathway regulatory motif
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 Regulator...
Citation: Journal of Clinical Bioinformatics 2013 3:20 -
Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks
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 ...
Citation: Journal of Clinical Bioinformatics 2013 3:19 -
Using biomarkers to predict progression from clinically isolated syndrome to multiple sclerosis
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 ex...
Citation: Journal of Clinical Bioinformatics 2013 3:18 -
Potential identification of pediatric asthma patients within pediatric research database using low rank matrix decomposition
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 ...
Citation: Journal of Clinical Bioinformatics 2013 3:16