PEPOP: Computational design of immunogenic peptides

Background  

Most methods available to predict protein epitopes are sequence based. There is a need for methods using 3D information for prediction of discontinuous epitopes and derived immunogenic peptides.     

High-throughput identification of interacting protein-protein binding sites

Background  

With the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Therefore, methods that are able to identify whether these binding sites interact are needed.     

Comparison study of microarray meta-analysis methods

Background  

Meta-analysis methods exist for combining multiple microarray datasets. However, there are a wide range of issues associated with microarray meta-analysis and a limited ability to compare the performance of different meta-analysis methods.     

Quantitative comparison of DNA detection by GFP-lac repressor tagging,fluorescence in situ hybridization and immunostaining

Background  

GFP-fusion proteins and immunostaining are methods broadly applied to investigate the three-dimensional organization of cells and cell nuclei, the latter often studied in addition by fluorescence in situ hybridization (FISH). Direct comparisons of these detection methods are scarce, however.     

A discriminative method for protein remote homology detection and fold recognition combining Top-<Emphasis Type="Italic">n</Emphasis>-grams and latent semantic analysis

Background  

Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences.     

Preferred analysis methods for Affymetrix GeneChips revealed by a wholly defined control dataset

Background  

As more methods are developed to analyze RNA-profiling data, assessing their performance using control datasets becomes increasingly important.     

Exploration of phylogenetic data using a global sequence analysis method

Background  

Molecular phylogenetic methods are based on alignments of nucleic or peptidic sequences. The tremendous increase in molecular data permits phylogenetic analyses of very long sequences and of many species, but also requires methods to help manage large datasets.     

Application of methods of identifying receptor binding models and analysis of parameters

Background  

Possible methods for distinguishing receptor binding models and analysing their parameters are considered.     

Stability of gene contributions and identification of outliers in multivariate analysis of microarray data

Background  

Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes.     

The Flp double cross system a simple efficient procedure for cloning DNA fragments

Background  

While conventional cloning methods using restriction enzymes and polynucleotide ligase are adequate for most DNAs, fragments made by the polymerase chain reaction are difficult to clone because the amplifying DNA polymerase tends to add untemplated nucleotides to the 3'-termini of the amplified strands. Conservative site-specific recombinases offer an efficient alternative to conventional cloning methods.     

Serial counts of Mycobacterium tuberculosis in sputum as surrogate markers of the sterilising activity of rifampicin and pyrazinamide in treating pulmonary tuberculosis

Background  

Since the sterilising activity of new antituberculosis drugs is difficult to assess by conventional phase III studies, surrogate methods related to eventual relapse rates are required.     

Comparative Analysis of Protein Structure Alignments

Background  

Several methods are currently available for the comparison of protein structures. These methods have been analysed regarding the performance in the identification of structurally/evolutionary related proteins, but so far there has been less focus on the objective comparison between the alignments produced by different methods.     

Quadratic regression analysis for gene discovery and pattern recognition for non-cyclic short time-course microarray experiments

Background  

Cluster analyses are used to analyze microarray time-course data for gene discovery and pattern recognition. However, in general, these methods do not take advantage of the fact that time is a continuous variable, and existing clustering methods often group biologically unrelated genes together.     

New resampling method for evaluating stability of clusters

Background  

Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in clustering procedures. Statistical methods are required to distinguish between real and random clusters. Several methods for assessing cluster stability have been published, including resampling methods such as the bootstrap.     

miR-Q: a novel quantitative RT-PCR approach for the expression profiling of small RNA molecules such as miRNAs in a complex sample

Background  

MicroRNAs (miRNAs) are small endogenous non-coding interfering RNA molecules regarded as major regulators in eukaryotic gene expression. Different methods are employed for miRNA expression profiling. For a better understanding of their role in essential biological processes, convenient methods for differential miRNA expression analysis are required.     

Parameter estimation in biochemical systems models with alternating regression

Background  

The estimation of parameter values continues to be the bottleneck of the computational analysis of biological systems. It is therefore necessary to develop improved methods that are effective, fast, and scalable.     

A comparison of probe-level and probeset models for small-sample gene expression data

Background  

Statistical methods to tentatively identify differentially expressed genes in microarray studies typically assume larger sample sizes than are practical or even possible in some settings.