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PubMed2006

Bioinformatics for comprehensive finding and analysis of glycosyltransferases.

Bioinformatics is a very powerful tool in the field of glycoproteomics as well as genomics and proteomics. As a part of the Glycogene Project (GG project), we have developed a novel bioinformatics system for the comprehensive identification and in silico cloning of human glycogenes. Using our system, a total of 105 candidate human glycogenes were identified and then engineered for heterologous expression. Of these candidates, 38 recombinant proteins were successfully identified for their enzyme activity and substrate specificity. We also classified 47 out of 60 carbohydrate-active enzyme glycosyltransferase families into 4 superfamilies using the profile Hidden Markov Model method. On the basis of our classification and the relationship between glycosylation pathways and superfamilies, we propose the evolution of glycosyltransferases.

Algorithms↗

PubMed2005

Intellectual property strategy in bioinformatics and biochips.

Intellectual property rights are essential in today's technology-driven age. A strong intellectual property protection strategy is crucial in the bioinformatics and biochips technology spaces as monetary and temporal resources are tremendous in finding a blockbuster drug or gene therapy, as well as in deploying advanced biosensor and other medical systems. Current problems and intellectual property practice in the genomic space are presented and analyzed. Various strategy and solutions are proposed to guide bioinformatic and biochip companies in forming an aggressive strategy to protect one's intellectual property and competitive positioning.

Computational Biology↗

PubMed2006

Fatty acid metabolism pathway play an important role in carcinogenesis of human colorectal cancers by Microarray-Bioinformatics analysis.

The present study systematically explored metabolic pathways and altered expressions of genes speculatively participating in colorectal carcinogenesis by using a Microarray-Bioinformatic analysis methods. The results revealed that 157 genes were up-regulated and 281 genes were down-regulated in colorectal cancer (CRC). Gene Ontology (GO) and relevant bioinformatics tools indicated that the functional category to which 438 genes (12%; 438/3800) of the most frequent alteration belonged was metabolism. The analysis of 10 colorectal cancer tissue specimens demonstrated that genes involved in fatty acid metabolic pathways had high rates of overexpression. In addition, we stimulated CRL-1790 cell line with linoleic acid (a polyunsaturated fatty acid) for 12, 24, 48 and 72 h. Cell proliferation was elevated by 5, 25, 28 and 31% (P<0.05), respectively. Further analyses revealed that the genes increasingly expressed in the cell line included enoyl-Coenzyme A, hydratase/3-hydroxyacyl Coenzyme A dehydrogenase (EHHADH), enoyl Coenzyme A hydratase, short chain, 1, mitochondrial (ECHS1); glutaryl-Coenzyme A dehydrogenase (GCDH), acyl-Coenzyme A oxidase 2, branched chain (ACOX2); acyl-Coenzyme A dehydrogenase, C-2 to C-3 short chain precursor (ACADS); carnitine palmitoyltransferase 1B (CPT1B), acyl-CoA synthetase long-chain family member 5 (ACSL5), and cytochrome P450, family 4, subfamily A, and polypeptide 11 (CYP4A11) genes. This indicated that the stimulating effect of linoleic acid on cell proliferation was due to interference with the metabolic pathway of fatty acid metabolism. In conclusion, genes with altered expression levels in CRC were mainly associated with fatty acid metabolic pathways speculated to have an important role linked to carcinogenesis.

Aged↗

PubMed2004

Bioinformatics strategies for proteomic profiling.

Clinical proteomics is an emerging field that involves the analysis of protein expression profiles of clinical samples for de novo discovery of disease-associated biomarkers and for gaining insight into the biology of disease processes. Mass spectrometry represents an important set of technologies for protein expression measurement. Among them, surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI TOF-MS), because of its high throughput and on-chip sample processing capability, has become a popular tool for clinical proteomics. Bioinformatics plays a critical role in the analysis of SELDI data, and therefore, it is important to understand the issues associated with the analysis of clinical proteomic data. In this review, we discuss such issues and the bioinformatics strategies used for proteomic profiling.

Computational Biology↗

PubMed2004

Genome data mining of lactic acid bacteria: the impact of bioinformatics.

Lactic acid bacteria (LAB) have been widely used in food fermentations and, more recently, as probiotics in health-promoting food products. Genome sequencing and functional genomics studies of a variety of LAB are now rapidly providing insights into their diversity and evolution and revealing the molecular basis for important traits such as flavor formation, sugar metabolism, stress response, adaptation and interactions. Bioinformatics plays a key role in handling, integrating and analyzing the flood of 'omics' data being generated. Reconstruction of metabolic potential using bioinformatics tools and databases, followed by targeted experimental verification and exploration of the metabolic and regulatory network properties, are the present challenges that should lead to improved exploitation of these versatile food bacteria.

Adaptation, Biological↗

PubMed2004

The characterisation and functional analysis of the human glyoxalase-1 gene using methods of bioinformatics.

Methylglyoxal (MG), which forms MG-derived AGE, is elevated in diabetic subjects with vascular disease. Detoxification of MG occurs through the glyoxalase system incorporating glyoxalase-1 (GLO1) and glyoxalase-2. Perturbations of the glyoxalase-1 gene (GLO1) may result in vulnerability to vascular complications through alterations in AGE interactions. We used bioinformatics to predict the structure, function and genetic variation of GLO1. We identified a previously unreported exon. Seventy single nucleotide polymorphisms (SNPs) were identified bioinformatically. The amino acid substitution Ala 111 Glu was confirmed and predicted to be tolerant. Though no alternative splice variants were identified, novel multiple alternative transcription start sites and alternative 3' UTRs were demonstrated. Ubiquitous expression of GLO1 was confirmed. Conserved regulatory regions were predicted 5' to the transcription start site and in the distal promoter, and several predicted conserved transcription regulatory elements were suggested in the 5' UTR. This study of GLO1 demonstrates multiple sequence variants at DNA and mRNA levels, areas of sequence conservation and SNPs that are predicted to affect function. A differential ability of glyoxalase-1 to reduce the formation and subsequent interaction of AGEs may have a role in the structural and functional manifestations of diabetic vascular disease.

Amino Acid Sequence↗

PubMed2006

A qualitative study of the implementation of a bioinformatics tool in a biological research laboratory.

OBJECTIVE: To explore how the implementation of a comprehensive new bioinformatics analysis system would affect workflow, collaboration and information management in a small genetic research lab. DESIGN: This was a longitudinal qualitative study of seven individuals involved in genomic and proteomic research. The study data were gathered using the illuminative/responsive approach of immersion in the environment. Additional qualitative data were gathered using informal semi-structured interviews, participant observation in lab meetings, and direct observation of lab researchers engaged in specific tasks. MEASUREMENTS: Interview, observation and field note data were coded and analyzed based on three analysis perspectives. A subset of the data was independently evaluated by an external researcher to enhance the trustworthiness of results. RESULTS: Three reoccurring themes were observed in the study. (1) Satisfaction and acceptance of software tools tended to be role and goal specific. (2) The system was seen primarily as a measurement system rather than a "total laboratory analysis system". (3) Lab meetings deemphasized the system, preferring more traditional data analysis techniques. These themes support the observations that the system was not used to its full potential in the lab. CONCLUSION: Themes identified in this study suggest that sophisticated genetic researchers face similar problems of technology implementation as do professionals in other fields. We recommend that leadership support and on-going training and evolution of academic curricula can improve chances of bioinformatics analysis systems becoming used more effectively.

Computational Biology↗

PubMed2004

Synergy between medical informatics and bioinformatics: facilitating genomic medicine for future health care.

In this paper, we review the results of BIOINFOMED, a study funded by the European Commission (EC) with the purpose to analyse the different issues and challenges in the area where Medical Informatics and Bioinformatics meet. Traditionally, Medical Informatics has been focused on the intersection between computer science and clinical medicine, whereas Bioinformatics have been predominantly centered on the intersection between computer science and biological research. Although researchers from both areas have occasionally collaborated, their training, objectives and interests have been quite different. The results of the Human Genome and related projects have attracted the interest of many professionals, and introduced new challenges that will transform biomedical research and health care. A characteristic of the 'post genomic' era will be to correlate essential genotypic information with expressed phenotypic information. In this context, Biomedical Informatics (BMI) has emerged to describe the technology that brings both disciplines (BI and MI) together to support genomic medicine. In recognition of the dynamic nature of BMI, institutions such as the EC have launched several initiatives in support of a research agenda, including the BIOINFOMED study.

Biotechnology↗

PubMed2005

Bioinformatics and biological reality.

Many bioinformaticians seem to shy away from believing that we can have knowledge about a mind-independent biological reality. This paper attempts to show that this tendency is neither well-founded nor harmless. Even though most bioinformaticians work only with terms and concepts, they cannot altogether disregard the question whether these terms and concepts have any real referents. The paper consists of three parts. Part I clarifies three different positions in the philosophy of science with which it would be good for the philosophical outlook of bioinformaticians to become familiar, and it defends one of them, Karl Popper's epistemological realism. Part II discusses a distinction which is necessary for epistemological realism and is of practical importance for bioinformatics, the distinction between the use and mention of terms and concepts. Part III, finally, contains some brief concluding words about realism, both in general and in relation to bioinformatics.

Biology↗

PubMed2001

Ethnopharmacology and bioinformatic combination for leads discovery: application to phospholipase A(2) inhibitors.

A program combining ethnopharmacology and bioinformatic approaches has successfully been applied on anti-inflammatory activity. (i) An ethnobotanical study allowed the identification of several plants associated with putative anti-inflammatory properties as potential leads. (ii) On the other hand, it is well known that phospholipase A(2) is a target implicated in the pro-inflammatory process. Thus, (iii) some selected plant extracts were experimentally tested on phospholipase A(2). Finally, (iv) these experimental results combined with bioinformatic tools, such as database exploitation and molecular modeling, allowed to suggest that one compound, betulin and its oxidative form betulinic acid, might be responsible of the anti-PLA(2) activity. This suggestion was confirmed experimentally.

Chromatography, High Pressure Liquid↗

PubMed2004

The Zebrafish DVD Exchange Project: a bioinformatics initiative.

Scientists who study zebrafish currently have an acute need to increase the rate of visual data exchange within their international community. Although the Internet has provided a revolutionary transformation of information exchange, the Internet is at present unable to serve as a vehicle for the efficient exchange of massive amounts of visual information. Much like an overburdened public water system, the Internet has inherent limits to the services it can provide. It is possible, however, for zebrafishologists to develop and use virtual intranets (such as the approach we outlined in this chapter) to adapt to the growing informatics need of our expanding research community. We need to assess qualitatively the economics of visual bioinformatics in our research community and evaluate the benefit:investment ratio of our collective information-sharing activities. The development of the World Wide Web started in the early 1990s by particle physicists who needed to rapidly exchange visual information within their collaborations. However, because of current limitations in information bandwidth, the World Wide Web cannot be used to easily exchange gigabytes of visual information. The Zebrafish DVD Exchange Project is aimed at by-passing these limitations. Scientists are curiosity-driven tool makers as well as curiosity-driven tool users. We have the capacity to assimilate new tools, as well as to develop new innovations, to serve our collective research needs. As a proactive research community, we need to create new data transfer methodologies (e.g., the Zebrafish DVD Exchange Project) to stay ahead of our bioinformatics needs.

Animals↗

PubMed2003

What is the relevance of bioinformatics to pharmacology?

Although bioinformatics achieved prominence because of its central role in genome data storage, management and analysis, its focus has shifted as the life sciences exploit these data. In pharmacology, genomic, transcriptomic and proteomic data are being used in the quest for drugs that fulfill unmet medical needs, are disease modifying or curative and are more effective and safer than current drugs. Bioinformatics is used in drug target identification and validation and in the development of biomarkers and toxicogenomic and pharmacogenomic tools to maximize the therapeutic benefit of drugs. Now that the 'parts list' of cellular signalling pathways is available, integrated computational and experimental programmes are being developed, with the goal of enabling in silico pharmacology by linking the genome, transcriptome and proteome to cellular pathophysiology.

Computational Biology↗

PubMedDate not supplied

Bioinformatics in glycobiology.

In comparison with genes and proteins, attention paid to oligosaccharides that modify proteins is still marginal. Accordingly, bioinformatics is so far poorly involved in glycobiology. Some initiatives have been taken, however, to collect in databases all glycobiology-relevant information or to design specific data mining algorithms to infer predictions or identify oligosaccharide structures. In this review, we make a non-exhaustive survey of the available glycobiology-related bioinformatic resources, focussing mainly on those resources that are available through the World Wide Web. Some well-curated databases are identified, but the development of specialised algorithms appears to be limited.

Algorithms↗

PubMed1997

Isomorphism between cell and human languages: molecular biological, bioinformatic and linguistic implications.

The concept of cell language has been defined in molecular terms. The molecule-based cell language is shown to be isomorphic with the sound- and visual signal-based human language with respect to ten out of the 13 design features of human language characterized by Hockett. Biocybernetics, a general molecular theory of living systems developed over the past two and a half decades, is found to provide a physical theory underlying the phenomenon of cell language. The concept of cell language integrates bioenergetics and bioinformatics on the one hand and reductionistic and holistic experimental data on the other to account for living processes on the molecular level. The isomorphism between cell and human languages suggests that the DNA of higher eucaryotes contains two classes of genes--structural genes corresponding to the lexicon and 'spatiotemporal genes' corresponding to the grammar of cell language. The former is located in coding regions of DNA and the latter is predicted to reside primarily in noncoding regions. The grammar of cell language is identified with the mapping of the nucleotide sequences of DNA onto its 4-dimensional folding patterns that control the spatiotemporal evolution of gene expression. Such a mapping has been referred to as the second genetic code, in contrast to the first genetic code which maps nucleotide triplets onto amino acids. The cell language theory introduces into biology the linguistic principle of 'rule-governed creativity,' leading to the formulation of the concept of 'rule-governed creative molecules' or 'creations.' This concept sheds new light on molecular biology, bioinformatics, protein folding, and developmental biology. In addition, the cell language theory suggests that human language is ultimately founded on cell language.

Cell Biology↗

PubMed2000

Computer applications in biomolecular sciences. Part 2: bioinformatics and genome projects.

This article defines and describes some of the basics of bioinformatics and projects aimed at sequencing entire genomes. Emphasis is placed on some of the ways in which the primary structures of nucleic acids and proteins may be investigated and analysed to gain meaningful biological information using computers and appropriate software. The importance of the world wide net and access to it is given prominence, particularly in bioinformatics research and teaching.

Journal Article↗

PubMed2003

Exploring the immunogenome with bioinformatics.

A better description of the immune system can be afforded if the latest developments in bioinformatics are applied to integrate sequence with structure and function. Clear guidelines for the upgrade of the bioinformatic capability of the immunogenetics laboratory are discussed in the light of more powerful methods to detect homology, combined approaches to predict the three dimensional properties of a protein and a robust strategy to represent the biological role of a gene.

Animals↗

PubMed2004

Bioinformatics and cancer target discovery.

The convergence of genomic technologies and the development of drugs designed against specific molecular targets provides many opportunities for using bioinformatics to bridge the gap between biological knowledge and clinical therapy. Identifying genes that have properties similar to known targets is conceptually straightforward. Additionally, genes can be linked to cancer via recurrent genomic or genetic abnormalities. Finally, by integrating large and disparate datasets, gene-level distinctions can be made between the different biological states that the data represents. These bioinformatics approaches and their associated methodologies, which can be applied across a range of technologies, facilitate the rapid identification of new target leads for further experimental validation.

Analysis of Variance↗

PubMed2000

Using bioinformatics in gene and drug discovery.

Bioinformatics has, out of necessity, become a key aspect of drug discovery in the genomic revolution, contributing to both target discovery and target validation. The author describes the role that bioinformatics has played and will continue to play in response to the waves of genome-wide data sources that have become available to the industry, including expressed sequence tags, microbial genome sequences, model organism sequences, polymorphisms, gene expression data and proteomics. However, these knowledge sources must be intelligently integrated.

Journal Article↗