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PubMed2005

Bioinformatics challenges in proteomics.

A little after the genomic revolution had been celebrated, it seemed as if a competition began to found new -omics disciplines that ultimately all have the same goal, the understanding of biological function. There are many similar definitions for proteomics that can be summarized as follows: proteomics is a large-scale study of structure and function of proteins in an organism or cell. Importantly, the proteome is much more variable than the genome through its interactions with the genome and secondary modifications. It differs depending on the tissue and stage in life-cycle. Hence, proteomics is a very diverse discipline that uses a variety of experimental set-ups and targets in order to elucidate function. Its dissociation from other disciplines can only remain artificial. The bioinformatics applied to proteomics are equally varied. In this review we will focus mainly on a few areas of bioinformatics that seem to us as particularly noteworthy or characteristic for proteomics research, for example in 2DE analysis or mass spectrometry. Another important task of bioinformatics is the prediction of functional properties. We will summarize the approaches taken in order to predict protein networks, which are based on the extensive integration of several kinds of -omics data. We will give a short overview of a demanding field in computational biology, the analysis and prediction of protein 3D structures. In order to provide a broader perspective we will close this review with a generalized description of activities and databases in the realm of proteomics.

Animals↗

PubMed2004

Bioinformatics in proteomics.

Proteomics technologies are under continuous improvements and new technologies are introduced. Nowadays high throughput acquisition of proteome data is possible. The young and rapidly emerging field of bioinformatics in proteomics is introducing new algorithms to handle large and heterogeneous data sets and to improve the knowledge discovery process. For example new algorithms for image analysis of two dimensional gels have been developed within the last five years. Within mass spectrometry data analysis algorithms for peptide mass fingerprinting (PMF) and peptide fragmentation fingerprinting (PFF) have been developed. Local proteomics bioinformatics platforms emerge as data management systems and knowledge bases in Proteomics. We review recent developments in bioinformatics for proteomics with emphasis on expression proteomics.

Animals↗

PubMed2000

A library-based bioinformatics services program.

Support for molecular biology researchers has been limited to traditional library resources and services in most academic health sciences libraries. The University of Washington Health Sciences Libraries have been providing specialized services to this user community since 1995. The library recruited a Ph.D. biologist to assess the molecular biological information needs of researchers and design strategies to enhance library resources and services. A survey of laboratory research groups identified areas of greatest need and led to the development of a three-pronged program: consultation, education, and resource development. Outcomes of this program include bioinformatics consultation services, library-based and graduate level courses, networking of sequence analysis tools, and a biological research Web site. Bioinformatics clients are drawn from diverse departments and include clinical researchers in need of tools that are not readily available outside of basic sciences laboratories. Evaluation and usage statistics indicate that researchers, regardless of departmental affiliation or position, require support to access molecular biology and genetics resources. Centralizing such services in the library is a natural synergy of interests and enhances the provision of traditional library resources. Successful implementation of a library-based bioinformatics program requires both subject-specific and library and information technology expertise.

Computational Biology↗

PubMed1999

Developmental bioinformatics: linking genetic data to virtual embryos.

This paper discusses current efforts to produce databases of gene expression for the major model embryos used in developmental biology. The efforts to build these resources were motivated by the need for immediate internet access to all types of research data, and the production of these databases is a major and new challenge for bioinformatics. Thus far bioinformatics has mainly been concerned with textually oriented resources and data, much of it concerned with gene and protein sequences. Because the genetic basis of developmental biology is integrated with developmental anatomy, these databases require the use of images to link molecular data with spatial information. In order to standardise database formats, digital atlases of some model systems are being produced that include integrated anatomical descriptions and these are being linked to appropriate genetic data. Integrating such image-based, searchable data into databases makes new demands on the field of bioinformatics and we consider here the imaging modalities that are used to obtain information and we discuss in particular the production of 3D images from serial sections. Next, we consider how to integrate textual and spatial descriptions of gene expression and the key tool needed to make this possible, i.e. anatomical nomenclature. A short review of internet resources on developmental biology is also given and future prospects for the development of these databases are discussed.

Animals↗

PubMed2001

[Bioinformatics analysis of autophagy 5 gene structure].

In order to study the relationship between autophagy and apoptosis, APG5 gene structure was revealed by bioinformatics analysis and meantime a new isoform resulted from alternative splicing of the hAPG5 gene was confirmed, which was hereby designated as human autophagy 5 beta (hAPG5 beta; LOCUS AF293841, GenBank). We cloned and sequenced the cDNAs from fetal brain and B cell cDNA libraries using the known hAPG5 cDNA open reading frame sequences as primers. The cDNA obtained from the human fetal brain cDNA library was identical to the known hAPG5 cDNA. However, the cDNA from adult brain cDNA library was 129 bp shorter in length, lacking the sequence corresponding to those from positions 434 to 563 of the hAPG5 cDNA. Through search in public database and sequence comparisons and assembly 4 related sequences, APG5 genomic sequence was obtained. We found that the hAPG5 gene had 8 exons, and those sequences missing in hAPG5 beta cDNA exactly corresponded to exon 3. By bioinformatics software, the structure of introns, exons, splicing sites, promoter and polyA were demonstrated. Moreover, we were able to express both hAGP5 and 5 beta cDNA clones in human hepatocytes and HeLa cells using pEGFP-C1 vector. In conclusion, our data indicate that a systematic bioinformatics method of finding protein diversity from alternative splicing is a good approach in post-genome biology.

Amino Acid Sequence↗

PubMed2002

Delivering bioinformatics training: bridging the gaps between computer science and biomedicine.

Biomedical researchers have always sought innovative methodologies to elucidate the underlying biology in their experimental models. As the pace of research has increased with new technologies that 'scale-up' these experiments, researchers have developed acute needs for the information technologies which assist them in managing and processing their experiments and results into useful data analyses that support scientific discovery. The application of information technology to support this discovery process is often called bioinformatics. We have observed a 'gap' in the training of those individuals who traditionally aid in the delivery of information technology at the level of the end-user (e.g. a systems analyst working with a biomedical researcher) which can negatively impact the successful application of technological solutions to biomedical research problems. In this paper we describe the roots and branches of bioinformatics to illustrate a range of applications and technologies that it encompasses. We then propose a taxonomy of bioinformatics as a framework for the identification of skills employed in the field. The taxonomy can be used to assess a set of skills required by a student to traverse this hierarchy from one area to another. We then describe a curriculum that attempts to deliver the identified skills to a broad audience of participants, and describe our experiences with the curriculum to show how it can help bridge the 'gap'.

Computational Biology↗

PubMed2002

Ontologies for molecular biology and bioinformatics.

About five years ago, ontology was almost unknown in bioinformatics, even more so in molecular biology. Nowadays, many bioinformatics articles mention it in connection with text mining, data integration or as a metaphysical cure for problems in standardisation of nomenclature and other applications. This article attempts to give an account of what concept ontologies in the domain of biology and bioinformatics are; what they are not; how they can be constructed; how they can be used; and some fallacies and pitfalls creators and users should be aware of.

Computational Biology↗

PubMed2003

Combining medical informatics and bioinformatics toward tools for personalized medicine.

OBJECTIVES: Key bioinformatics and medical informatics research areas need to be identified to advance knowledge and understanding of disease risk factors and molecular disease pathology in the 21 st century toward new diagnoses, prognoses, and treatments. METHODS: Three high-impact informatics areas are identified: predictive medicine (to identify significant correlations within clinical data using statistical and artificial intelligence methods), along with pathway informatics and cellular simulations (that combine biological knowledge with advanced informatics to elucidate molecular disease pathology). RESULTS: Initial predictive models have been developed for a pilot study in Huntington's disease. An initial bioinformatics platform has been developed for the reconstruction and analysis of pathways, and work has begun on pathway simulation. CONCLUSIONS: A bioinformatics research program has been established at GE Global Research Center as an important technology toward next generation medical diagnostics. We anticipate that 21 st century medical research will be a combination of informatics tools with traditional biology wet lab research, and that this will translate to increased use of informatics techniques in the clinic.

Biomedical Research↗

PubMed2002

Virus bioinformatics: databases and recent applications.

Bioinformatics is now used as an umbrella term for almost all aspects of computational biology. Bioinformatics research will have an impact on all of biology, and virology is not immune from these research methods. Although virology has been slower to embrace bioinformatics this is now changing, particularly in the areas of viral sequences databasing and the systematic identification of viral and host homologous proteins. Here we will review some of these recent advances focusing mainly on the herpesvirus.

Computational Biology↗

PubMed2002

Towards a bioinformatics network for Latin America and the Caribbean (LACBioNet).

Bioinformatics is increasingly recognised as a crucial field for research and development in the biological sciences, and forms an integral part of genomics, proteomics and modern biotechnology. Worldwide participation is important, and scientists in developing countries can contribute to this field. Regional networks for bioinformatics are highly beneficial for capacity strengthening and cooperation, and for establishing productive interactions between scientists in the fields of biological and informatics sciences. Such a network (LACBioNet) is being organised for Latin America and the Caribbean. Its immediate goals include the organisation and extension of nodes and services, information and communication, research and development in different specialty fields of bioinformatics, and training and human resource development.

Caribbean Region↗

PubMed2004

Bioinformatics: perspectives for the future.

I give here a very personal perspective of Bioinformatics and its future, starting by discussing the origin of the term (and area) of bioinformatics and proceeding by trying to foresee the development of related issues, including pattern recognition/data mining, the need to reintegrate biology, the potential of complex networks as a powerful and flexible framework for bioinformatics and the interplay between bio- and neuroinformatics. Human resource formation and market perspective are also addressed. Given the complexity and vastness of these issues and concepts, as well as the limited size of a scientific article and finite patience of the reader, these perspectives are surely incomplete and biased. However, it is expected that some of the questions and trends that are identified will motivate discussions during the IcoBiCoBi round table (with the same name as this article) and perhaps provide a more ample perspective among the participants of that conference and the readers of this text.

Bioethics↗

PubMed2005

[Gene regulation and bioinformatics].

Gene regulation networks control differentiation and function of hundreds of cell types. Dysfunctions of transcription factors, which are key elements in the regulation pathways, are involved in numerous pathologies. The recent development of genomics technologies allows the study of gene regulation mechanisms and help us understand their impact on the cells. Bioinformatic tools are needed to fully exploit data obtained by genomics approaches. Thus, bioinformatics play an essential role in the characterisation of the transcription factors binding sites and their target genes. In this review we will introduce the main breakthroughs in bioinformatics area for the comprehension of regulation mechanisms. We will insist on i) the approaches "with a priori" for the genome annotation based on known transcription factors binding sites, ii) the approaches "without a priori" for the discovery of new binding sites and iii) the functional annotation of the target genes of those transcription factors. Finally, we will present recent examples of the fruitful use of in silico studies for the comprehension of regulation mechanisms and of the consequences of their dysfunction.

Algorithms↗

PubMedDate not supplied

[The apology of bioinformatics].

The discussion about adequate understanding of the term "bioinformatics" is continued. The relationships between bioinformatics and experimental molecular biology are considered. The list of the main branches and achievements of modern bioinformatics is presented.

Computational Biology↗

PubMed2006

[Bioinformatics analysis of YZ-2 and preparation of polyclonal antibody].

AIM: To analyze YZ-2, a novel protein associated with cerebral ischemia and prepares its polyclonal antibody. METHODS: According to the bioinformatics analysis and prediction of the possible high structure, hydrophilicity and antigenicity of YZ-2, a 22-amino acid residue partial peptide of YZ-2 was synthesized. The synthesized peptide was then used to immunize. And the properties of anti-YZ2 were analyzed by ELISA and Western blot. RESULTS: The hydrophilicity and antigenicity were predicted by methods of bioinformatics. The polyclonal antibody of YZ-2 was successfully obtained and its specificity and sensitivity were conformed by ELISA and Western blot. CONCLUSION: By the bioinformatics analysis and prediction, the hydrophilicity and antigenicity of YZ2 were analyzed. The antibody of YZ-2 was successfully obtained.

Animals↗

PubMed2006

Current bioinformatics tools in genomic biomedical research (Review).

On the advent of a completely assembled human genome, modern biology and molecular medicine stepped into an era of increasingly rich sequence database information and high-throughput genomic analysis. However, as sequence entries in the major genomic databases currently rise exponentially, the gap between available, deposited sequence data and analysis by means of conventional molecular biology is rapidly widening, making new approaches of high-throughput genomic analysis necessary. At present, the only effective way to keep abreast of the dramatic increase in sequence and related information is to apply biocomputational approaches. Thus, over recent years, the field of bioinformatics has rapidly developed into an essential aid for genomic data analysis and powerful bioinformatics tools have been developed, many of them publicly available through the World Wide Web. In this review, we summarize and describe the basic bioinformatics tools for genomic research such as: genomic databases, genome browsers, tools for sequence alignment, single nucleotide polymorphism (SNP) databases, tools for ab initio gene prediction, expression databases, and algorithms for promoter prediction.

Computational Biology↗

PubMed1996

Identification through bioinformatics of cDNAs encoding human thymic shared Ag-1/stem cell Ag-2. A new member of the human Ly-6 family.

The Ly-6 family of cell surface molecules includes many members that have been characterized in the mouse. Until recently, very few Ly-6 family members had been described in the human. A significant development with important implications for novel gene discovery has been the growth of the public Expressed Sequence Tag (EST) database. Here we report that, through the application of bioinformatics analysis to the dbEST database, we obtained the sequence of human TSA-1/SCA-2, a new member of the human Ly-6 family. In addition, we identified full-length clones encoding this molecule as well as expression data in various tissues. Sequencing of the clones identified this way confirmed the sequence predicted through bioinformatics. This study constitutes an example of the application of bioinformatics to the analysis of the recently expanded databases for the identification of genes of potential importance in the immune system.

Amino Acid Sequence↗

PubMed2025

Unlocking microbial potential: advances in omics and bioinformatics for aromatic hydrocarbon degradation.

Aromatic hydrocarbons (AHs) are persistent environmental pollutants with high toxicity. Bacterial degradation of AHs provides a sustainable and cost-effective approach for the remediation of sites contaminated with both mono- and polycyclic aromatic hydrocarbons. Aerobic degradation of AHs typically involves oxygenases-mediated hydroxylation followed by aromatic ring cleavage. In contrast, anaerobic degradation relies on diverse activation mechanisms that ultimately converge on the central intermediate benzoyl-CoA. Over the past decades, research on bacterial degradation of AHs has grown steadily, supported by advances in omics and bioinformatics. In this review, we summarize the current knowledge on the pathways, enzymes, and microbial diversity involved in AH degradation, highlighting how omics and bioinformatic approaches are advancing our understanding of this process. However, to improve our knowledge of microbial AHs catabolism, it is crucial to prioritize the characterization of novel enzymes and pathways, especially those mediating anaerobic and hybrid degradation strategies. Addressing this gap requires the development of specialized resources that incorporate a broader taxonomic diversity and an expanded inventory of anaerobic genes and enzymes supported by experimental evidence. Equally important is the integration of multi-omics technologies, artificial intelligence, and ecological modeling into unified analytical pipelines. These efforts will be key to fully unlocking microbial metabolic potential and guiding more effective bioremediation and monitoring strategies for AHs.

Biodegradation, Environmental↗

PubMed2026

Screening and identification of key genes related to the immune microenvironment of rectal cancer influenced by radiotherapy based on bioinformatics methods.

OBJECTIVE: Radiotherapy (RT) plays a crucial role in the comprehensive treatment of rectal cancer. However, the impact of radiotherapy on the tumor microenvironment (TME), especially its effect on immune cell infiltration and immune-related gene expression, has not been fully studied. This study aims to screen and analyze key genes related to the immune microenvironment of rectal cancer influenced by radiotherapy based on bioinformatics methods for the purpose of identifying potential biomarkers and providing new insights for the personalized therapy of rectal cancer. METHODS: Using data from the Public Gene Expression Database (GEO) and the Cancer Genomics Database (TCGA), the impact of radiotherapy on the immune microenvironment of rectal cancer was explored using bioinformatics tools. Through screening differentially expressed genes (DEGs), correlation analysis, TIMER database analysis, immune infiltration score, and correlation analysis between key genes and prognosis, the effects of radiotherapy on the immune microenvironment of rectal cancer were investigated. RESULTS: Totally 7 upregulated and 4 downregulated differentially expressed genes were identified, among which MASP1, LTK, SLC9A3R2 were negatively correlated with myeloid suppressor cell infiltration (MDSCs), while ZP2 was positively correlated. The expression of MASP1 and SLC9A3R2 was closely related to the level of immune cell infiltration and played significant roles in the immune microenvironment. High expression of MASP1 was significantly correlated with survival benefits from immune checkpoint inhibitor therapy, while SLC9A3R2 was closely related to the efficacy of PD-L1 inhibitors and CTLA4 inhibitors. CONCLUSIONS: MASP1 and SLC9A3R2, as two key genes that may be related to the immune microenvironment of rectal cancer radiotherapy, deserve further exploration of their roles in the mechanism. The combination of radiotherapy and immunotherapy holds promising prospects in the treatment of rectal cancer, and exploration of related mechanisms will provide new strategies and targets for the treatment of various tumors and rectal cancer.

Bioinformatics↗