Pattern recognition in the computer analysis of nucleotide sequences

We have used an algorithm from the pattern recognition theory "generalized portrait" to find a distinguishing vector for Escherichia coli promoters. We have made an attempt to solve closely linked problems for choosing significant signs of that signal, multiple alignment and for calculation of the recognition vector (matrix). The promoters with known strength have been ranged with this vector. The analysis of the occurrence of predicted promoters has been carried out. The promoters search program for IBM-compatible computers is available from the authors.     

Evolution of MIR Elements Located in the Coding Regions of Human Genome

A search for new members of the mammalian interspersed repeat (MIR) family has been done over the coding regions of human genome from GenBank-116. Only 254 nucleotide sequences contained MIRs in coding regions, of which 45 MIR copies were unknown before, including 17 that occurred in translated gene regions. The program developed by the authors has been demonstrated to surpass the CENSOR program in the search power. The evolution of the MIR copies located in translated regions of human genome is discussed.     

Evolution of MIR-repeats in coding regions of the human genome]

A search for new members of the mammalian interspersed repeat (MIR) family has been done over the coding regions of human genome from GenBank-116. Only 254 nucleotide sequences contained MIRs in coding regions, of which 45 MIR copies were unknown before, including 17 that occurred in translated gene regions. The program developed by the authors has been demonstrated to surpass the CENSOR program in the search power. The evolution of the MIR copies located in translated regions of human genome is discussed.     

In Silico analysis of the lateral organ junction (LOJ) gene and promoter of Arabidopsis thaliana

A T-DNA based promoter trapped mutant has led to the identification of a novel lateral organ junction specific promoter upstream of the pentatricopeptide repeat (PPR) protein coding gene LOJ in Arabidopsis thaliana by our laboratory. Various in silico based prediction tools are employed to characterize the upstream sequence of the LOJ gene. Out of numerous cis-elements detected in the LOJ promoter a few are considered important based on the expression pattern of the LOJ gene. These elements would provide a basis for designing experiments for more accurate promoter function annotation. A comparative search for conserved elements in the 5'-upstream region of a few genes involved in lateral organ development and meristem related expression reveals a few common relevant regulatory motifs. The coding region of the LOJ gene is intron-less and contains 19 PPR units. Based on in silico analysis, LOJ protein is predicted to be hydrophobic in nature and targeted to mitochondria. A partial 3D model of LOJ protein has been suggested using a homology-based modeling program.     

OrthoFocus: program for identification of orthologs in multiple genomes in family-focused studies

The identification of orthologs to a set of known genes is often the starting point for evolutionary studies focused on gene families of interest. To date, the existing orthology detection tools (COG, InParanoid, OrthoMCL, etc.) are aimed at genome-wide ortholog identification and lack flexibility for the purposes of case studies. We developed a program OrthoFocus, which employs an extended reciprocal best hit approach to quickly search for orthologs in a pair of genomes. A group of paralogs from the input genome is used as the start for the forward search and the criterion for the reverse search, which allows handling many-to-one and many-to-many relationships. By pairwise comparison of genomes with the input species genome, OrthoFocus enables quick identification of orthologs in multiple genomes and generates a multiple alignment of orthologs so that it can further be used in phylogenetic analysis. The program is available at http://www.lipidomics.ru/.     

On the impact of the distance between two genes on their interaction curve

We analyze a basic building block of gene regulatory networks using a stochastic/geometric model in search of a mathematical backing for the discrete modeling frameworks. We consider a network consisting only of two interacting genes: a source gene and a target gene. The target gene is activated by the proteins encoded by the source gene. The interaction is therefore mediated by activator proteins that travel, like a signal, from the source to the target. We calculate the production curve of the target proteins in response to a constant-rate production of activator proteins. The latter has a sigmoidal shape (like a simple delay line) that is sharper and taller when the two genes are closer to each other. This provides further support for the use of discrete models in the analysis gene regulatory networks. Moreover, it suggests an evolutionary pressure towards making the interacting genes closer to each other to make their interactions more efficient and more reliable.     

Similarity searches in genome-wide numerical data sets

   

We present psi-square, a program for searching the space of gene vectors. The program starts with a gene vector, i.e., the set of measurements associated with a gene, and finds similar vectors, derives a probabilistic model of these vectors, then repeats search using this model as a query, and continues to update the model and search again, until convergence. When applied to three different pathway-discovery problems, psi-square was generally more sensitive and sometimes more specific than the ad hoc methods developed for solving each of these problems before.     

Dragon Gene Start Finder identifies approximate locations of the 5' ends of genes

Recognition of gene starts is a difficult and yet unsolved problem. We present a program, Dragon Gene Start Finder (DGSF), which assesses the gene start in mammalian genomes and predicts a region which should overlap with the first exon of the gene or be in its proximity. The program has been rigorously tested on human chromosomes 4, 21 and 22, and in a strand specific search achieves an overall sensitivity of approximately 65% and a positive predictive value of approximately 78%. The sensitivity for the CpG-island related promoters is >88%. DGSF is free for academic and non-profit users at http://sdmc.lit.org.sg/promoter/dragonGSF1_0/genestart.htm; the download version of the program integrated within the TRANSPLORER package can be obtained from Biobase GmbH, at http://www.biobase.de/.     

Identification and expression analysis of EST-based genes in the bud of Lycoris longituba

To obtain a primary overview of gene diversity and expression pattern in Lycoris longituba, 4,992 ESTs (Expressed Sequence Tags) from L. longituba bud were sequenced and 4,687 cleaned ESTs were used for gene expression analysis. Clustered by the PHRAP program, 967 contigs and 1,343 singlets were obtained. Blast search showed that 179 contigs and 227 singlets (totally 1,066 ESTs) had homologues in GenBank and 3,621 ESTs were novel.     

TranScout: prediction of gene expression regulatory proteins from their sequences

MOTIVATION: The advent of genomics yields thousands of reading frames in search of function. Identification of conserved functional motifs in protein sequences can be helpful for function prediction. RESULTS: A database and a classification of reported DNA-binding protein motifs has been designed. A program ('TranScout') has been developed for the detection and evaluation of conserved motifs in prokaryotic and eukaryotic sequences of proteins with a gene regulatory function. The efficiency of the program is shown in a benchmark against a database obtained from SWISS-PROT without the protein sequences used to train the program. All motifs were detected with a mean average sensitivity of 0.98 and a mean average specificity of 0.92. AVAILABILITY: The program is freely available for use on the internet at http://luz.uab.es/transcout/. The user can find additional information at this site.     

PKB: a program system and data base for analysis of protein structure

PKB is a computer program system that combines a data base of three-dimensional protein structures with a series of algorithms for pattern recognition, data analysis, and graphics. By typing relatively simple commands the user may search the data base for instances of a structural motif and analyze in detail the set of individual structures that are found. The application of PKB to the study of protein folding is illustrated in three examples. The first analysis compares the conformations observed for a short sequential motif, sequences similar to the cell-attachment signal Arg-Gly-Asp. The second compares sequences observed for a conformational motif, a 16-residue beta alpha beta unit. The third analysis considers a population of substructures containing ion-pair interactions, examining the relationship of frequency of occurrence to calculated electrostatic energy.     

MASCOT HTML and XML parser: an implementation of a novel object model for protein identification data

Protein identification using MS is an important technique in proteomics as well as a major generator of proteomics data. We have designed the protein identification data object model (PDOM) and developed a parser based on this model to facilitate the analysis and storage of these data. The parser works with HTML or XML files saved or exported from MASCOT MS/MS ions search in peptide summary report or MASCOT PMF search in protein summary report. The program creates PDOM objects, eliminates redundancy in the input file, and has the capability to output any PDOM object to a relational database. This program facilitates additional analysis of MASCOT search results and aids the storage of protein identification information. The implementation is extensible and can serve as a template to develop parsers for other search engines. The parser can be used as a stand-alone application or can be driven by other Java programs. It is currently being used as the front end for a system that loads HTML and XML result files of MASCOT searches into a relational database. The source code is freely available at http://www.ccbm.jhu.edu and the program uses only free and open-source Java libraries.     

From Data towards Knowledge: Revealing the Architecture of Signaling Systems by Unifying Knowledge Mining and Data Mining of Systematic Perturbation Data

Genetic and pharmacological perturbation experiments, such as deleting a gene and monitoring gene expression responses, are powerful tools for studying cellular signal transduction pathways. However, it remains a challenge to automatically derive knowledge of a cellular signaling system at a conceptual level from systematic perturbation-response data. In this study, we explored a framework that unifies knowledge mining and data mining towards the goal. The framework consists of the following automated processes: 1) applying an ontology-driven knowledge mining approach to identify functional modules among the genes responding to a perturbation in order to reveal potential signals affected by the perturbation; 2) applying a graph-based data mining approach to search for perturbations that affect a common signal; and 3) revealing the architecture of a signaling system by organizing signaling units into a hierarchy based on their relationships. Applying this framework to a compendium of yeast perturbation-response data, we have successfully recovered many well-known signal transduction pathways; in addition, our analysis has led to many new hypotheses regarding the yeast signal transduction system; finally, our analysis automatically organized perturbed genes as a graph reflecting the architecture of the yeast signaling system. Importantly, this framework transformed molecular findings from a gene level to a conceptual level, which can be readily translated into computable knowledge in the form of rules regarding the yeast signaling system, such as “if genes involved in the MAPK signaling are perturbed, genes involved in pheromone responses will be differentially expressed.”     

候选抑瘤基因 BRD7 及家族蛋白的功能研究进展

溴区结构（bromodomain）是近年来发现的广泛分布于多种生物中的一种高度保守的结构域,溴区结构蛋白通过参与信号依赖性的基因转录调控而广泛参与细胞内重要的生命活动．BRD7基因是1999年克隆的一个新的bromodomain基因,GenBank登录号为AF152604或AF152605．eMotif分析表明,BRD7蛋白包含多个磷酸化位点和一个保守bromodomain功能域,Blast显示BRD7蛋白与人的Celtix-1及鼠的bromodomain蛋白BP75具有高度的同源性．利用转基因技术已证实,在鼻咽癌细胞系HNEl中过表达BRD7基因可以抑制其细胞生长和细胞周期G1-S的进程,并部分逆转鼻咽痛细胞HNE1的恶性表型．为了全面地揭示BRD7基因的细胞内生物学功能,深入了解BRD7基因的细胞内整体信息流向,中南大学肿瘤研究所细胞遗传室已从上、中、下游三个不同层面对BRD7基因的功能研究展开了初步的探索．     

MedMiner: an Internet text-mining tool for biomedical information, with application to gene expression profiling

The trend toward high-throughput techniques in molecular biology and the explosion of online scientific data threaten to overwhelm the ability of researchers to take full advantage of available information. This problem is particularly severe in the rapidly expanding area of gene expression experiments, for example, those carried out with cDNA microarrays or oligonucleotide chips. We present an Internet-based hypertext program, MedMiner, which filters and organizes large amounts of textual and structured information returned from public search engines like GeneCards and PubMed. We demonstrate the value of the approach for the analysis of gene expression data, but MedMiner can also be extended to other areas involving molecular genetic or pharmacological information. More generally still, MedMiner can be used to organize the information returned from any arbitrary PubMed search.     

候选抑瘤基因 BRD7 及家族蛋白的功能研究进展

溴区结构(bromodomain)是近年来发现的广泛分布于多种生物中的一种高度保守的结构域,溴区结构蛋白通过参与信号依赖性的基因转录调控而广泛参与细胞内重要的生命活动.BRD7基因是1999年克隆的一个新的bromodomain基因,GenBank登录号为AF152604或AF152605.eMotif分析表明,BRD7蛋白包含多个磷酸化位点和一个保守bromodomain功能域,Blast显示BRD7蛋白与人的Celtix-1及鼠的bromodomain蛋白BP75具有高度的同源性.利用转基因技术已证实,在鼻咽癌细胞系HNE1中过表达BRD7基因可以抑制其细胞生长和细胞周期G1-S的进程,并部分逆转鼻咽癌细胞HNE1的恶性表型.为了全面地揭示BRD7基因的细胞内生物学功能,深入了解BRD7基因的细胞内整体信息流向,中南大学肿瘤研究所细胞遗传室已从上、中、下游三个不同层面对BRD7基因的功能研究展开了初步的探索.     

A Fourier analysis of symmetry in protein structure

The score matrix from a structure comparison program (SAP) was used to search for repeated structures using a Fourier analysis. When tested with artificial data, a simple Fourier transform of the smoothed matrix provided a clear signal of the repeat periodicity that could be used to extract the repeating units with the SAP program. The strength of the Fourier signal was calibrated against the signal from model proteins. The most useful of these was the novel random-walk approach employed to generate realistic 'fake' structures. On the basis of these it was possible to conclude that only a small proportion of protein structures have an unexpected degree of symmetry. Artificially generated 'ideal' folds provided an upper limit on the strength of signal that could be expected from a 'perfectly' repeating compact structure. Unexpectedly, some of the very regular beta-propellor folds attained the same strength but the majority of symmetric structures lay below this region. When native proteins were ranked by the power of their spectrum a wide variety of fold types were seen to score highly. In the betaalpha class, these included the globular betaalpha proteins and the more repetitive leucine-rich betaalpha folds. In the all-beta class; beta-propellors, beta-prisms and beta-helices were found as well as the more globular gamma-crystalin domains. When this ranked list was filtered to remove proteins that contained detectable internal sequence similarity (using the program REPRO), the list became exclusively composed of just globular betaalpha class proteins and in the top 50 re-ranked proteins, only a single 4-fold propellor structure remained.     

A metabolic network analysis & NMR experiment design tool with user interface-driven model construction for depth-first search analysis

A Windows program for metabolic engineering analysis and experimental design has been developed. A graphical user interface enables the pictorial, "on-screen" construction of a metabolic network. Once a model is composed, balance equations are automatically generated. Model construction, modification and information exchange between different users is thus considerably simplified. For a given model, the program can then be used to predict all the extreme point flux distributions that optimize an objective function while satisfying balances and constraints by using a depth-first search strategy. One can also find the minimum reaction set that satisfies different conditions. Based on the identified flux distributions or linear combinations, the user can simulate the NMR and GC/MS spectra of selected signal molecules. Alternately, spectra vectorization allows for the automated optimization of labeling experiments that are intended to distinguish between different, yet plausible flux extreme point distributions. The example provided entails predicting the flux distributions associated with deleting pyruvate kinase and designing 13C NMR experiments that can maximally discriminate between the flux distributions.