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At least 1,603 records · Page 89Linked to original sources

PubMed2003

PF-IND: probability algorithm and software for separation of plant and fungal sequences.

The separation of plant and fungal sequences in EST pools by bioinformatic methods is difficult because of sequence similarities between plants and fungi, lack of enough sequence information, and the short length of the isolated fragments. An algorithm and software that utilize the differences in codon usage bias to discriminate between plant and fungal sequences are described. The software (PF-IND) includes five pairs of fungi and their host plants that can be used to analyze a large number of related species. Analysis of a sequence provides an arbitrary value that defines the likelihood that a sequence will be a fungal or a plant gene. The software can distinguish between homologous fungal and plant genes and it helps identify the correct reading frame of unknown expressed sequence tags (ESTs) for which BLAST analyses do not provide clear information. Short sequences of 100-150 bp can be analyzed with high confidence. PF-IND analysis of 100 sequences derived from fungal infected plants identified the origin of 94 sequences. Only 66 sequences were identified by a BLASTX analysis of the same 100 ESTs. Overall, PF-IND is a novel bioinformatic tool aimed at assisting the research of fungus-plant interactions.

Algorithms↗

PubMed2002

[The use of gene expression differential display analysis technics in trauma research].

Gene is the regulation core of cell proliferation, differentiation and maturation. It is also the decisive factor of occurrence, progression and prognosis of many diseases. The changes in gene expression will inevitably lead to many kinds of abnormal in cells, tissue, organs even in whole biological organism. Trauma, as well as other stimulators, may bring a series complications through the abnormal expression of genes following injury. With the development of bioinformatics and molecular biology, a series of assays (so called gene expression differential display analysis technics, such as DNA microarray) have been established, which have been used to analyze differentially expressed genes effectively. These methods have been widely used in the research of tumor and other disease. This review will focus to some usage of the ways in traumatology.

Animals↗

PubMed2005

Bioinformatic methods to exploit mass spectrometric data for proteomic applications.

The new technologies in mass spectrometric analysis of peptides and proteins necessary to accommodate proteomics-scale analyses require, in turn, concomitant development of informatics technologies suitable for very large-scale data handling and analysis. This chapter focuses on the data analysis tools available to the community for analysis of mass spectrometric proteomics data. Different database searching strategies are discussed for peptide and protein identification, and approaches and tools available for comparative quantitative analysis of samples are outlined.

Animals↗

PubMed2006

A bioinformatics pipeline for high-throughput microbial multilocus sequence typing (MLST) analyses.

Multilocus sequence typing (MLST) analysis for semi-routine applications is hindered by the downstream, manually intensive steps of processing the raw sequence data files. This report describes the development of an MLST pipeline that automates DNA sequence editing and analysis in order to significantly reduce the time required for processing data. Validation using a pneumococcal dataset revealed complete agreement between the results generated by manual and automated workflows. The MLST pipeline was developed for both double-strand and single-strand sequencing.

Bacteria↗

PubMed1998

TAMBIS--Transparent Access to Multiple Bioinformatics Information Sources.

The TAMBIS project aims to provide transparent access to disparate biological databases and analysis tools, enabling users to utilize a wide range of resources with the minimum of effort. A prototype system has been developed that includes a knowledge base of biological terminology (the biological Concept Model), a model of the underlying data sources (the Source Model) and a 'knowledge-driven' user interface. Biological concepts are captured in the knowledge base using a description logic called GRAIL. The Concept Model provides the user with the concepts necessary to construct a wide range of multiple-source queries, and the user interface provides a flexible means of constructing and manipulating those queries. The Source Model provides a description of the underlying sources and mappings between terms used in the sources and terms in the biological Concept Model. The Concept Model and Source Model provide a level of indirection that shields the user from source details, providing a high level of source transparency. Source independent, declarative queries formed from terms in the Concept Model are transformed into a set of source dependent, executable procedures. Query formulation, translation and execution is demonstrated using a working example.

Artificial Intelligence↗

PubMed2002

Molecular biologist's guide to proteomics.

The emergence of proteomics, the large-scale analysis of proteins, has been inspired by the realization that the final product of a gene is inherently more complex and closer to function than the gene itself. Shortfalls in the ability of bioinformatics to predict both the existence and function of genes have also illustrated the need for protein analysis. Moreover, only through the study of proteins can posttranslational modifications be determined, which can profoundly affect protein function. Proteomics has been enabled by the accumulation of both DNA and protein sequence databases, improvements in mass spectrometry, and the development of computer algorithms for database searching. In this review, we describe why proteomics is important, how it is conducted, and how it can be applied to complement other existing technologies. We conclude that currently, the most practical application of proteomics is the analysis of target proteins as opposed to entire proteomes. This type of proteomics, referred to as functional proteomics, is always driven by a specific biological question. In this way, protein identification and characterization has a meaningful outcome. We discuss some of the advantages of a functional proteomics approach and provide examples of how different methodologies can be utilized to address a wide variety of biological problems.

Amino Acid Sequence↗

PubMed2006

Mouse orthologs of human olfactory-like receptors expressed in the tongue.

Olfactory-like receptors (OLRs) have been shown previously to be expressed in adult and foetal human tongue. This prompted us to verify the hypothesis if OLRs were involved in taste perception. In the present work, the mouse orthologs of OLR genes expressed in adult and/or foetal human tongue were identified. Analysis of their genomic localization and of their primary sequence features using bioinformatics did not reveal any shared remarkable characteristic. The expression of eight of these orthologs (S25/mJCG1, K42, mJCG2, mJCG3, P2/mJCG5, P3/mJCG6, mT09m/mJCG9, K21/mTPCR85 and mTPCR06) was studied in three types of mouse papillae as well as in the olfactory epithelium. It was found that all of them are expressed in olfactory epithelium and that only three of them (S25/mJCG1, K42/mJCG2 and mTPCR06) are expressed in papillae. However, despite many efforts it was impossible to detect without ambiguity the presence of OLR mRNAs in taste receptor cells nor in surrounding tissues by in-situ hybridization. Hence, the studied OLRs very likely play in taste papillae other roles than taste perception.

Adult↗

PubMed2004

A high productivity/low maintenance approach to high-performance computation for biomedicine: four case studies.

The rapid advances in high-throughput biotechnologies such as DNA microarrays and mass spectrometry have generated vast amounts of data ranging from gene expression to proteomics data. The large size and complexity involved in analyzing such data demand a significant amount of computing power. High-performance computation (HPC) is an attractive and increasingly affordable approach to help meet this challenge. There is a spectrum of techniques that can be used to achieve computational speedup with varying degrees of impact in terms of how drastic a change is required to allow the software to run on an HPC platform. This paper describes a high- productivity/low-maintenance (HP/LM) approach to HPC that is based on establishing a collaborative relationship between the bioinformaticist and HPC expert that respects the former's codes and minimizes the latter's efforts. The goal of this approach is to make it easy for bioinformatics researchers to continue to make iterative refinements to their programs, while still being able to take advantage of HPC. The paper describes our experience applying these HP/LM techniques in four bioinformatics case studies: (1) genome-wide sequence comparison using Blast, (2) identification of biomarkers based on statistical analysis of large mass spectrometry data sets, (3) complex genetic analysis involving ordinal phenotypes, (4) large-scale assessment of the effect of possible errors in analyzing microarray data. The case studies illustrate how the HP/LM approach can be applied to a range of representative bioinformatics applications and how the approach can lead to significant speedup of computationally intensive bioinformatics applications, while making only modest modifications to the programs themselves.

Amino Acid Sequence↗

PubMed2006

Predicting candidate genes for human deafness disorders: a bioinformatics approach.

BACKGROUND: There are more than 50 genes for autosomal dominant and autosomal recessive nonsyndromic hereditary deafness that are yet to be cloned. The human genome sequence and expression profiles of transcripts in the inner ear have aided positional cloning approaches. The knowledge of protein interactions offers additional advantages in selecting candidate genes within a mapped region. RESULTS: We have employed a bioinformatic approach to assemble the genes encoded by genomic regions that harbor various deafness loci. The genes were then in silico analyzed for their candidacy by expression pattern and ability to interact with other proteins. Such analyses have narrowed a list of 2400 genes from suspected regions of the genome to a manageable number of about 140 for further analysis. CONCLUSION: We have established a list of strong candidate genes encoded by the regions linked to various nonsyndromic hereditary hearing loss phenotypes by using a novel bioinformatic approach. The candidates presented here provide a starting point for mutational analysis in well-characterized families along with genetic linkage to refine the loci. The advantages and shortcomings of this bioinformatic approach are discussed.

Chromosome Mapping↗

PubMed2006

Phenotypic and global gene expression profile changes between low passage and high passage MIN-6 cells.

The long-term potential to routinely use replacement beta cells/islets as cell therapy for type 1 diabetes relies on our ability to culture such cells/islets, in vitro, while maintaining their functional status. Previous beta cell studies, by ourselves and other researchers, have indicated that the glucose-stimulated insulin secretion (GSIS) phenotype is relatively unstable, in long-term culture. This study aimed to investigate phenotypic and gene expression changes associated with this loss of GSIS, using the MIN-6 cell line as model. Phenotypic differences between MIN-6(L, low passage) and MIN-6(H, high passage) were determined by ELISA (assessing GSIS and cellular (pro)insulin content), proliferation assays, phase contrast light microscopy and analysis of alkaline phosphatase expression. Differential mRNA expression was investigated using microarray, bioinformatics and real-time PCR technologies. Long-term culture was found to be associated with many phenotypic changes, including changes in growth rate and cellular morphology, as well as loss of GSIS. Microarray analyses indicate expression of many mRNAs, including many involved in regulated secretion, adhesion and proliferation, to be significantly affected by passaging/ long-term culture. Loss/reduced levels, in high passage cells, of certain transcripts associated with the mature beta cell, together with increased levels of neuron/glia-associated mRNAs, suggest that, with time in culture, MIN-6 cells may revert to an early (possibly multi-potential), poorly differentiated, 'precursor-like' cell type. This observation is supported by increased expression of the stem cell marker, alkaline phosphatase.

Alkaline Phosphatase↗

PubMed2005

Detection and reduction of evolutionary noise in correlated mutation analysis.

Direct or indirect inter-residue interactions in proteins are often reflected by mutations at one site that compensate for mutations at another site. Various bioinformatic methods have been developed for detecting such correlated mutations in order to obtain information about intra- and inter-protein interactions. Here, we show by carrying out a correlated mutation analysis for non-interacting proteins that the signal due to inter-residue interactions is of similar magnitude to the 'noise' that arises from other evolutionary processes related to common ancestry. A new method for detecting correlated mutations is presented that reduces this evolutionary noise by taking into account evolutionary distances in the protein family. It is shown that this method yields better signal-to-noise ratios and, therefore, can much better resolve, for example, correlated mutations that reflect true inter-residue interactions.

Computational Biology↗

PubMed2005

Inferential literacy for experimental high-throughput biology.

Many biologists believe that data analysis expertise lags behind the capacity for producing high-throughput data. One view within the bioinformatics community is that biological scientists need to develop algorithmic skills to meet the demands of the new technologies. In this article, we argue that the broader concept of inferential literacy, which includes understanding of data characteristics, experimental design and statistical analysis, in addition to computation, more adequately encompasses what is needed for efficient progress in high-throughput biology.

Animals↗

PubMed2004

The molecular scanner: concept and developments.

Approaches aimed at deciphering the proteome have illustrated the need for relatively complex and highly sensitive methodologies. The major elements of proteome analysis, such as powerful protein separation and enzymatic processing, mass spectrometry and dedicated bioinformatics have been assembled in the development of the molecular scanner. This highly flexible and data-rich approach has combined the power of electrophoretic protein separation, the simultaneous digestion and transfer of proteins through an enzymatic membrane, the immediate use of the MALDI mass spectrometer to scan a collecting membrane, and the development of dedicated bioinformatics tools to perform protein identification and molecular imaging of the proteome. Clinical applications of the molecular scanner have also started to be developed for disease diagnosis in biological material.

Animals↗

PubMed2026

Transcriptomic and network analyses identify epigenetic regulators of drug-tolerant persister (DTP) subsets in EGFR-mutant HCC827 non-small cell lung cancer.

BACKGROUND: The clinical efficacy of osimertinib, a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI), in EGFR-mutant non-small cell lung cancer (NSCLC) is limited by the inevitable acquired resistance. Drug-tolerant persister (DTP) cells, which survive initial therapy, are considered a key reservoir for this resistance. Understanding the molecular characteristics of DTPs is essential for developing strategies to prevent relapse. OBJECTIVE: This study aimed to characterize the transcriptomic landscape of osimertinib-tolerant DTP cells and identify key epigenetic regulators associated with the DTP phenotype in EGFR-mutant HCC827 NSCLC cells through integrated transcriptomic and network analyses. METHODS: We established an in vitro model of osimertinib tolerance using an EGFR-mutant (exon 19 deletion) HCC827 NSCLC cell line. Parental HCC827 cells and DTP subsets were subjected to transcriptomic analysis by RNA sequencing (RNA-seq). Differentially expressed genes were identified, followed by bioinformatics analyses, including Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein interaction (PPI) network analyses to identify key biological processes driving the DTP phenotype. Key findings were validated using quantitative real-time PCR (qPCR). RESULTS: Osimertinib treatment induced a morphologically distinct DTP population. Transcriptomic profiling revealed a marked shift in gene expression compared to parental cells. Functional enrichment analysis showed significant upregulation of epigenetic pathways. PPI network analysis identified a core module of eight hub genes, including histone deacetylases (HDAC5, HDAC9), sirtuins (SIRT1, SIRT2), and histone acetyltransferase (KAT2B). qPCR confirmed increased expression of HDAC5, HDAC9, and SIRT1. CONCLUSION: Epigenetic reprogramming accompanies the transition to an osimertinib-tolerant state in EGFR-mutant HCC827 cells. Targeting HDACs and sirtuins may represent a promising strategy to eliminate DTP subpopulations and delay or prevent acquired resistance.

Drug-tolerant persister↗

PubMed2005

Genetic programs activated by proneural proteins in the developing Drosophila PNS.

Neurogenesis depends on a family of proneural transcriptional activator proteins, but the "proneural" function of these factors is poorly understood, in part because the ensemble of genes they activate, directly or indirectly, has not been identified systematically. We have taken a direct approach to this problem in Drosophila. Fluorescence-activated cell sorting was used to recover a purified population of the cells that comprise the "proneural clusters" from which sensory organ precursors of the peripheral nervous system (PNS) arise. Whole-genome microarray analysis and in situ hybridization was then used to identify and verify a set of genes that are preferentially expressed in proneural cluster cells. Genes in this set encode proteins with a diverse array of implied functions, and loss-of-function analysis of two candidate genes shows that they are indeed required for normal PNS development. Bioinformatic and reporter gene studies further illuminate the cis-regulatory codes that direct expression in proneural clusters.

Animals↗

PubMed2005

Genomic organization and molecular analysis of virulent bacteriophage 2972 infecting an exopolysaccharide-producing Streptococcus thermophilus strain.

The Streptococcus thermophilus virulent pac-type phage 2972 was isolated from a yogurt made in France in 1999. It is a representative of several phages that have emerged with the industrial use of the exopolysaccharide-producing S. thermophilus strain RD534. The genome of phage 2972 has 34,704 bp with an overall G+C content of 40.15%, making it the shortest S. thermophilus phage genome analyzed so far. Forty-four open reading frames (ORFs) encoding putative proteins of 40 or more amino acids were identified, and bioinformatic analyses led to the assignment of putative functions to 23 ORFs. Comparative genomic analysis of phage 2972 with the six other sequenced S. thermophilus phage genomes confirmed that the replication module is conserved and that cos- and pac-type phages have distinct structural and packaging genes. Two group I introns were identified in the genome of 2972. They interrupted the genes coding for the putative endolysin and the terminase large subunit. Phage mRNA splicing was demonstrated for both introns, and the secondary structures were predicted. Eight structural proteins were also identified by N-terminal sequencing and/or matrix-assisted laser desorption ionization-time-of-flight mass spectrometry. Detailed analysis of the putative minor tail proteins ORF19 and ORF21 as well as the putative receptor-binding protein ORF20 showed the following interesting features: (i) ORF19 is a hybrid protein, because it displays significant identity with both pac- and cos-type phages; (ii) ORF20 is unique; and (iii) a protein similar to ORF21 of 2972 was also found in the structure of the cos-type phage DT1, indicating that this structural protein is present in both S. thermophilus phage groups. The implications of these findings for phage classification are discussed.

Amino Acid Sequence↗

PubMed2001

Parasite genome initiatives.

During 1993-1994, scientists from developing and developed countries planned and initiated a number of parasite genome projects and several consortiums for the mapping and sequencing of these medium-sized genomes were established, often based on already ongoing scientific collaborations. Financial and other support came from WHO/TDR, Wellcome Trust and other funding agencies. Thus, the genomes of Plasmodium falciparum, Schistosoma mansoni, Trypanosoma cruzi, Leishmania major, Trypanosoma brucei, Brugia malayi and other pathogenic nematodes are now under study. From an initial phase of network formation, mapping efforts and resource building (EST, GSS, phage, cosmid, BAC and YAC library constructions), sequencing was initiated in gene discovery projects but soon also on a small chromosome, and now on a fully fledged genome scale. Proteomics, functional analysis, genetic manipulation and microarray analysis are ongoing to different degrees in the respective genome initiatives, and as the funding for the whole genome sequencing becomes secured, most of the participating laboratories, apart from larger sequencing centres, become oriented to post-genomics. Bioinformatics networks are being expanded, including in developing countries, for data mining, annotation and in-depth analysis.

Animals↗

PubMed2006

[High throughput screening and analysis of prostate cancer-related genes through mining databases].

BACKGROUND & OBJECTIVE: Investigation of differentially expressed genes in prostate cancer tissues may help to understand the molecular mechanism of prostate cancer and provide diagnostic markers or new targets for therapy. The Cancer Genome Anatomy Project (CGAP) public database provides an unprecedented opportunity for cancer researchers to mine genes differentially expressed in cancer tissues by bioinformatic methods. This study was to explore the feasibility of incorporating the Internet-available Serial Analysis of Gene Expression (SAGE) and cDNA databases to find human prostate cancer-related genes. METHODS: SAGE digital gene expression displayer (DGED) and cDNA DGED were used to analyze differentially expressed (>5 folds) genes in malignant prostate tissues compared with normal prostate tissues. The SAGE tags were filtered by their confidence and our 3 criteria. To test the confidence of tags of virtual digital analysis for gene identification, the modified GLGI (generation of longer cDNA fragments from SAGE tags for gene identification) was used to get the cDNA 3' end downstream of 20 tags. Main functions of all candidate genes and their relations to prostate cancer were annotated. RESULTS: Fifty-three differentially expressed genes were screened out by SAGE DGED, 26 of them were up-regulated and 27 were down-regulated in prostate cancer; 28 differentially expressed genes were got by cDNA DGED, 15 of them were up-regulated and 13 were down-regulated in prostate cancer. CONCLUSION: Reasonable use of public databases by the Internet-available tools is a simple, effective approach to get cancer-related genes, and might provide useful clues for further investigation although the results require experimental validation.

DNA, Complementary↗