Identification of biomarkers from mass spectrometry data using a "common" peak approach

Background  

Proteomic data obtained from mass spectrometry have attracted great interest for the detection of early-stage cancer. However, as mass spectrometry data are high-dimensional, identification of biomarkers is a key problem.     

Array-A-Lizer: A serial DNA microarray quality analyzer

Background  

The proliferate nature of DNA microarray results have made it necessary to implement a uniform and quick quality control of experimental results to ensure the consistency of data across multiple experiments prior to actual data analysis.     

Validation of rheumatoid arthritis diagnoses in health care utilization data

Introduction  

Health care utilization databases have been increasingly used for studies of rheumatoid arthritis (RA). However, the accuracy of RA diagnoses in these data has been inconsistent.     

Comparison of protein interaction networks reveals species conservation and divergence

Background  

Recent progresses in high-throughput proteomics have provided us with a first chance to characterize protein interaction networks (PINs), but also raised new challenges in interpreting the accumulating data.     

SIMPROT: Using an empirically determined indel distribution in simulations of protein evolution

Background  

General protein evolution models help determine the baseline expectations for the evolution of sequences, and they have been extensively useful in sequence analysis and for the computer simulation of artificial sequence data sets.     

Web-based interrogation of gene expression signatures using EXALT

Background  

Widespread use of high-throughput techniques such as microarrays to monitor gene expression levels has resulted in an explosive growth of data sets in public domains. Integration and exploration of these complex and heterogeneous data have become a major challenge.     

Bayesian and maximum likelihood phylogenetic analyses of protein sequence data under relative branch-length differences and model violation

Background  

Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets. We have investigated the performance of Bayesian inference with empirical and simulated protein-sequence data under conditions of relative branch-length differences and model violation.     

Providing visualisation support for the analysis of anatomy ontology data

Background  

Improvements in technology have been accompanied by the generation of large amounts of complex data. This same technology must be harnessed effectively if the knowledge stored within the data is to be retrieved. Storing data in ontologies aids its management; ontologies serve as controlled vocabularies that promote data exchange and re-use, improving analysis.     

Testing the additional predictive value of high-dimensional molecular data

Background  

While high-dimensional molecular data such as microarray gene expression data have been used for disease outcome prediction or diagnosis purposes for about ten years in biomedical research, the question of the additional predictive value of such data given that classical predictors are already available has long been under-considered in the bioinformatics literature.     

Transcript-based redefinition of grouped oligonucleotide probe sets using AceView: High-resolution annotation for microarrays

Background  

Extracting biological information from high-density Affymetrix arrays is a multi-step process that begins with the accurate annotation of microarray probes. Shortfalls in the original Affymetrix probe annotation have been described; however, few studies have provided rigorous solutions for routine data analysis.     

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method

Background  

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general.     

A knowledge discovery object model API for Java

Background  

Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized.     

GenMAPP 2: new features and resources for pathway analysis

Background  

Microarray technologies have evolved rapidly, enabling biologists to quantify genome-wide levels of gene expression, alternative splicing, and sequence variations for a variety of species. Analyzing and displaying these data present a significant challenge. Pathway-based approaches for analyzing microarray data have proven useful for presenting data and for generating testable hypotheses.     

VANTED: A system for advanced data analysis and visualization in the context of biological networks

Background  

Recent advances with high-throughput methods in life-science research have increased the need for automatized data analysis and visual exploration techniques. Sophisticated bioinformatics tools are essential to deduct biologically meaningful interpretations from the large amount of experimental data, and help to understand biological processes.     

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

Background  

There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights.     

Unsupervised statistical clustering of environmental shotgun sequences

Background  

The development of effective environmental shotgun sequence binning methods remains an ongoing challenge in algorithmic analysis of metagenomic data. While previous methods have focused primarily on supervised learning involving extrinsic data, a first-principles statistical model combined with a self-training fitting method has not yet been developed.     

SAQC: SNP Array Quality Control

Background  

Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed.     

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

Background  

Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult.