GOTree Machine (GOTM): a web-based platform for interpreting sets of interesting genes using Gene Ontology hierarchies

Background  

Microarray and other high-throughput technologies are producing large sets of interesting genes that are difficult to analyze directly. Bioinformatics tools are needed to interpret the functional information in the gene sets.     

MASPECTRAS: a platform for management and analysis of proteomics LC-MS/MS data

Background  

The advancements of proteomics technologies have led to a rapid increase in the number, size and rate at which datasets are generated. Managing and extracting valuable information from such datasets requires the use of data management platforms and computational approaches.     

Discover protein sequence signatures from protein-protein interaction data

Background  

The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-protein interaction (PPI) datasets. Mining these datasets for underlying biological knowledge has, however, remained a challenge.     

Expression profiling of human renal carcinomas with functional taxonomic analysis

Background  

Molecular characterization has contributed to the understanding of the inception, progression, treatment and prognosis of cancer. Nucleic acid array-based technologies extend molecular characterization of tumors to thousands of gene products. To effectively discriminate between tumor sub-types, reliable laboratory techniques and analytic methods are required.     

Discover Protein Complexes in Protein-Protein Interaction Networks Using Parametric Local Modularity

Background  

Recent advances in proteomic technologies have enabled us to create detailed protein-protein interaction maps in multiple species and in both normal and diseased cells. As the size of the interaction dataset increases, powerful computational methods are required in order to effectively distil network models from large-scale interactome data.     

PCR-based gene synthesis to produce recombinant proteins for crystallization

Background  

Gene synthesis technologies are an important tool for structural biology projects, allowing increased protein expression through codon optimization and facilitating sequence alterations. Existing methods, however, can be complex and not always reproducible, prompting researchers to use commercial suppliers rather than synthesize genes themselves.     

MochiView: versatile software for genome browsing and DNA motif analysis

Background  

As high-throughput technologies rapidly generate genome-scale data, it becomes increasingly important to visually integrate these data so that specific hypotheses can be formulated and tested.     

A database and API for variation,dense genotyping and resequencing data

Background  

Advances in sequencing and genotyping technologies are leading to the widespread availability of multi-species variation data, dense genotype data and large-scale resequencing projects. The 1000 Genomes Project and similar efforts in other species are challenging the methods previously used for storage and manipulation of such data necessitating the redesign of existing genome-wide bioinformatics resources.     

Ultra-high throughput sequencing-based small RNA discovery and discrete statistical biomarker analysis in a collection of cervical tumours and matched controls

Background  

Ultra-high throughput sequencing technologies provide opportunities both for discovery of novel molecular species and for detailed comparisons of gene expression patterns. Small RNA populations are particularly well suited to this analysis, as many different small RNAs can be completely sequenced in a single instrument run.     

Ovarian cancer classification based on dimensionality reduction for SELDI-TOF data

Background  

Recent advances in proteomics technologies such as SELDI-TOF mass spectrometry has shown promise in the detection of early stage cancers. However, dimensionality reduction and classification are considerable challenges in statistical machine learning. We therefore propose a novel approach for dimensionality reduction and tested it using published high-resolution SELDI-TOF data for ovarian cancer.     

The High Throughput Sequence Annotation Service (HT-SAS) – the shortcut from sequence to true Medline words

Background  

Advances in high-throughput technologies available to modern biology have created an increasing flood of experimentally determined facts. Ordering, managing and describing these raw results is the first step which allows facts to become knowledge. Currently there are limited ways to automatically annotate such data, especially utilizing information deposited in published literature.     

PanGEA: Identification of allele specific gene expression using the 454 technology

Background  

Next generation sequencing technologies hold great potential for many biological questions. While mainly used for genomic sequencing, they are also very promising for gene expression profiling. Sequencing of cDNA does not only provide an estimate of the absolute expression level, it can also be used for the identification of allele specific gene expression.     

Edge detection in microscopy images using curvelets

Background  

Despite significant progress in imaging technologies, the efficient detection of edges and elongated features in images of intracellular and multicellular structures acquired using light or electron microscopy is a challenging and time consuming task in many laboratories.     

Bioinformatics strategies for lipidomics analysis: characterization of obesity related hepatic steatosis

Background  

Lipids are an important and highly diverse class of molecules having structural, energy storage and signaling roles. Modern analytical technologies afford screening of many lipid molecular species in parallel. One of the biggest challenges of lipidomics is elucidation of important pathobiological phenomena from the integration of the large amounts of new data becoming available.     

High-throughput sequence alignment using Graphics Processing Units

Background  

The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies.     

Definition of an automated Content-Based Image Retrieval (CBIR) system for the comparison of dermoscopic images of pigmented skin lesions

Background  

New generations of image-based diagnostic machines are based on digital technologies for data acquisition; consequently, the diffusion of digital archiving systems for diagnostic exams preservation and cataloguing is rapidly increasing. To overcome the limits of current state of art text-based access methods, we have developed a novel content-based search engine for dermoscopic images to support clinical decision making.     

Recombinant human follicle-stimulating hormone produces more oocytes with a lower total dose per cycle in assisted reproductive technologies compared with highly purified human menopausal gonadotrophin: a meta-analysis

Background  

Human menopausal gonadotrophins and recombinant human follicle stimulating hormone are the two main gonadotrophin products utilized for controlled ovarian stimulation in assisted reproductive technologies. In this meta-analysis, the number of oocytes was designated as the most relevant endpoint directly resulting from ovarian stimulation, and therefore where the drug effect may be estimated with the best sensitivity.     

DecGPU: distributed error correction on massively parallel graphics processing units using CUDA and MPI

Background  

Next-generation sequencing technologies have led to the high-throughput production of sequence data (reads) at low cost. However, these reads are significantly shorter and more error-prone than conventional Sanger shotgun reads. This poses a challenge for the de novo assembly in terms of assembly quality and scalability for large-scale short read datasets.