Bioinformatics database infrastructure for biotechnology research

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.

NABIC: A New Access Portal to Search, Visualize, and Share Agricultural Genomics Data

The National Agricultural Biotechnology Information Center developed an access portal to search, visualize, and share agricultural genomics data with a focus on South Korean information and resources. The portal features an agricultural biotechnology database containing a wide range of omics data from public and proprietary sources. We collected 28.4 TB of data from 162 agricultural organisms, with 10 types of omics data comprising next-generation sequencing sequence read archive, genome, gene, nucleotide, DNA chip, expressed sequence tag, interactome, protein structure, molecular marker, and single-nucleotide polymorphism datasets. Our genomic resources contain information on five animals, seven plants, and one fungus, which is accessed through a genome browser. We also developed a data submission and analysis system as a web service, with easy-to-use functions and cutting-edge algorithms, including those for handling next-generation sequencing data.

Best use of experimental data in cancer informatics

The welcome attitude of the 'omics community, journals and funders of research towards data sharing, coupled with successful implementations of data standards, has resulted in resource dissemination and a better understanding of many diseases, including cancer. Sharing experiment data is beneficial in terms of knowledge generation, allowing reproduction and validation of results. An adherence to a reporting guideline enables full-value extraction from costly data; this is an inexpensive method to increased quality without incurring disproportionate costs. For therapy data in particular, easy access to the range of new approaches and the ability to perform valid comparisons between these approaches would be especially useful. We discuss initiatives that support resource sharing and summarize three reporting guidelines for experiment data that have been adopted successfully. Finally, we introduce a new guideline that encompasses the diverse data types in therapeutic experiments, which is intended to be of use to the cancer therapeutics community.

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein-carbohydrate interaction are reviewed.

Analysis of Domains in Selected Plant and Animal Food Proteins - Precursors of Biologically Active Peptides - In Silico Approach

In silico methods are useful tool in protein structure-functional relationships analysis. BIOPEP and InterPro databases were applied to analyze the presence of bioactive fragments in the domains occurring in the sequences representing the major groups of proteins. Domains found in the proteins analyzed had mostly transporting (bovine β-lactoglobulin), immunoglobulin-like (chicken connectin), alpha-amylase inhibitor (a/β-wheat gliadin), calcium binding (chicken myosin) functions, or allowed straightly to assign the protein to an appropriate superfamily (bovine casein). It confirmed the thesis about the existence of the functional relations between the structure (sequence) and the domains with identified conformation. Amongst the domains present in the protein sequences we revealed the presence of fragments with the activities: antihypertensive, opioid, dipeptidylpeptidase IV inhibitors, immunomodulating, and neuropeptides. In the chicken connectin within the immunoglobulin-like domain we found immunomodulating fragments. InterPro analysis did not reveal the existence of any domains in a soybean globulin. It can be explained by the lack of the key structure information helpful in the defining the structure-function relationships. As the number of information in the applied databases will continue to increase we can expect to find stronger relationships between bioactivity of fragments encrypted in proteins and the functionality of domains. This might allow in the future to find evolutionary similarity between different origin food proteins - sources of bioactive peptides.