Bioinformatics for Renal and Urinary Proteomics: Call for Aggrandization.

The clinical sampling of urine is noninvasive and unrestricted, whereby huge volumes can be easily obtained. This makes urine a valuable resource for the diagnoses of diseases. Urinary and renal proteomics have resulted in considerable progress in kidney-based disease diagnosis through biomarker discovery and treatment. This review summarizes the bioinformatics tools available for this area of proteomics and the milestones reached using these tools in clinical research. The scant research publications and the even more limited bioinformatic tool options available for urinary and renal proteomics are highlighted in this review. The need for more attention and input from bioinformaticians is highlighted, so that progressive achievements and releases can be made. With just a handful of existing tools for renal and urinary proteomic research available, this review identifies a gap worth targeting by protein chemists and bioinformaticians. The probable causes for the lack of enthusiasm in this area are also speculated upon in this review. This is the first review that consolidates the bioinformatics applications specifically for renal and urinary proteomics.

Insights into Bioinformatic Applications for Glycosylation: Instigating an Awakening towards Applying Glycoinformatic Resources for Cancer Diagnosis and Therapy.

Glycosylation plays a crucial role in various diseases and their etiology. This has led to a clear understanding on the functions of carbohydrates in cell communication, which eventually will result in novel therapeutic approaches for treatment of various disease. Glycomics has now become one among the top ten technologies that will change the future. The direct implication of glycosylation as a hallmark of cancer and for cancer therapy is well established. As in proteomics, where bioinformatics tools have led to revolutionary achievements, bioinformatics resources for glycosylation have improved its practical implication. Bioinformatics tools, algorithms and databases are a mandatory requirement to manage and successfully analyze large amount of glycobiological data generated from glycosylation studies. This review consolidates all the available tools and their applications in glycosylation research. The achievements made through the use of bioinformatics into glycosylation studies are also presented. The importance of glycosylation in cancer diagnosis and therapy is discussed and the gap in the application of widely available glyco-informatic tools for cancer research is highlighted. This review is expected to bring an awakening amongst glyco-informaticians as well as cancer biologists to bridge this gap, to exploit the available glyco-informatic tools for cancer.

Overview of software options for processing, analysis and interpretation of mass spectrometric proteomic data.

Recently, the interests in proteomics have been intensively increased, and the proteomic methods have been widely applied to many problems in cell biology. If the age of 1990s is considered to be a decade of genomics, we can claim that the following years of the new century is a decade of proteomics. The rapid evolution of proteomics has continued through these years, with a series of innovations in separation techniques and the core technologies of two-dimensional gel electrophoresis and MS. Both technologies are fueled by automation and high throughput computation for profiling of proteins from biological systems. As Patterson ever mentioned, 'data analysis is the Achilles heel of proteomics and our ability to generate data now outstrips our ability to analyze it'. The development of automatic and high throughput technologies for rapid identification of proteins is essential for large-scale proteome projects and automatic protein identification and characterization is essential for high throughput proteomics. This review provides a snap shot of the tools and applications that are available for mass spectrometric high throughput biocomputation. The review starts with a brief introduction of proteomics and MS. Computational tools that can be employed at various stages of analysis are presented, including that for data processing, identification, quantification, and the understanding of the biological functions of individual proteins and their dynamic interactions. The challenges of computation software development and its future trends in MS-based proteomics have also been speculated.

Computer applications making rapid advances in high throughput microbial proteomics (HTMP).

The last few decades have seen the rise of widely-available proteomics tools. From new data acquisition devices, such as MALDI-MS and 2DE to new database searching softwares, these new products have paved the way for high throughput microbial proteomics (HTMP). These tools are enabling researchers to gain new insights into microbial metabolism, and are opening up new areas of study, such as protein-protein interactions (interactomics) discovery. Computer software is a key part of these emerging fields. This current review considers: 1) software tools for identifying the proteome, such as MASCOT or PDQuest, 2) online databases of proteomes, such as SWISS-PROT, Proteome Web, or the Proteomics Facility of the Pathogen Functional Genomics Resource Center, and 3) software tools for applying proteomic data, such as PSI-BLAST or VESPA. These tools allow for research in network biology, protein identification, functional annotation, target identification/validation, protein expression, protein structural analysis, metabolic pathway engineering and drug discovery.