序列同源性分析软件Blast的WEB界面构建及其应用

基于局域网(Intranet)内的PC/Linux服务器, 构建了序列同源性分析软件Blast的WEB界面. 局域网内的所有计算机均可通过WEB方式访问该服务器进行公共数据库和自建数据库的查询,具有保密、高效、免费的优点,能够满足实验室和研究院所的大规模、快速数据分析任务.     

EST-based analysis of gene expression in the porcine brain

Since pig is an important livestock species worldwide, its gene expression has been investigated intensively, but rarely in brain. In order to study gene expression profiles in the pig central nervous system, we sequenced and analyzed 43,122 highquality 5’ end expressed sequence tags (ESTs) from porcine cerebellum, cortex cerebrum, and brain stem cDNA libraries, involving several different prenatal and postnatal developmental stages. The initial ESTs were assembled into 16,101 clusters and compared to protein and nucleic acid databases in GenBank. Of these sequences, 30.6% clusters matched protein databases and represented function known sequences; 75.1% had significant hits to nucleic acid databases and partial represented known function; 73.3% matched known porcine ESTs; and 21.5% had no matches to any known sequences in GenBank. We used the categories defined by the Gene Ontology to survey gene expression in the porcine brain.     

Detecting distant homologs using phylogenetic tree-based HMMs

It is often desired to identify further homologs of a family of biological sequences from the ever-growing sequence databases. Profile hidden Markov models excel at capturing the common statistical features of a group of biological sequences. With these common features, we can search the biological database and find new homologous sequences. Most general profile hidden Markov model methods, however, treat the evolutionary relationships between the sequences in a homologous group in an ad-hoc manner. We hereby introduce a method to incorporate phylogenetic information directly into hidden Markov models, and demonstrate that the resulting model performs better than most of the current multiple sequence-based methods for finding distant homologs.     

SWISS-PROT: connecting biomolecular knowledge via a protein database

With the explosive growth of biological data, the development of new means of data storage was needed. More and more often biological information is no longer published in the conventional way via a publication in a scientific journal, but only deposited into a database. In the last two decades these databases have become essential tools for researchers in biological sciences. Biological databases can be classified according to the type of information they contain. There are basically three types of sequence-related databases (nucleic acid sequences, protein sequences and protein tertiary structures) as well as various specialized data collections. It is important to provide the users of biomolecular databases with a degree of integration between these databases as by nature all of these databases are connected in a scientific sense and each one of them is an important piece to biological complexity. In this review we will highlight our effort in connecting biological information as demonstrated in the SWISS-PROT protein database.     

The protein identification resource (PIR)

The Protein Identification Resource consists of an integrated computer system composed of a number of protein and nucleic acid sequence databases and software designed for the identification and analysis of protein sequences and their corresponding coding sequences. The PIR serves the scientific community through on-line access, distributing magnetic tapes, and performing off-line sequence identification services for researchers.     

Statistical analysis of genome

The chemical structure of DNA is characterized by sequences of four basic nitrogens occurring in one of two nucleic acid chains and in a complementary fashion in the other. Markov chain is the aspect of probability theory that analyzes discrete states in which transition is a fixed probability not affected by the history of the system. It is shown that DNA is represented in the form of regular Markov chain. Ergodicity property and law of large numbers follow from the statistical analysis of stationary transition probabilities.     

On the distribution of the nucleotides in seven completely sequenced DNAs

Several Markov chain models (up to fourth order) have been fitted to the sequences of the seven DNAs presented in Fuchs et al. (1980). Two methods for determining the order of Markov chain are applied to the data. The two methods lead to different conclusions and we dicuss these discrepancies. When the distribution of the nucleotides in a DNA sequence is investigated, it is suggested that the study on the order of the Markov model should be supplemented with additional analysis.     

The protein identification resource (PIR).

The Protein Identification Resource, which provides the scientific community with an efficient on-line computer system designed for the identification and analysis of protein sequences and their corresponding coding sequences, has been established. The resource consists of an integrated computer system composed of a number of protein and nucleic acid sequence databases and the software necessary to analyze this information effectively.     

Bayesian selection of markov models for symbol sequences: application to microsaccadic eye movements

Complex biological dynamics often generate sequences of discrete events which can be described as a Markov process. The order of the underlying Markovian stochastic process is fundamental for characterizing statistical dependencies within sequences. As an example for this class of biological systems, we investigate the Markov order of sequences of microsaccadic eye movements from human observers. We calculate the integrated likelihood of a given sequence for various orders of the Markov process and use this in a Bayesian framework for statistical inference on the Markov order. Our analysis shows that data from most participants are best explained by a first-order Markov process. This is compatible with recent findings of a statistical coupling of subsequent microsaccade orientations. Our method might prove to be useful for a broad class of biological systems.     

On the distribution of the nucleotides in the seven completely sequenced DNAs

Several Markov chain models (up to fourth order) have been fitted to the sequences of the seven DNAs presented in Fuchs et al. (1980). Two methods for determining the order of Markov chain are applied to the data. The two methods lead to different conclusions and we dicuss these discrepancies. When the distribution of the nucleotides in a DNA sequence is investigated, it is suggested that the study on the order of the Markov model should be supplemented with additional analysis.     

A simple quantitative model of the molecular clock

Summary We present the ideas, and their motivation, at the basis of a simple model of nucleic acid evolution: thestationary Markov process, or Markov clock. After a brief review of its relevant mathematical properties, the Markov clock is applied to nucleotide sequences from mitochondrial and nuclear genes of different species. Particular emphasis is given to the necessity of carrying out a correct statistical analysis, which allows us to check quantitatively the applicability of our model. We find evidence that the Markov clock ticks in many different processes, and that its limitations can be understood in terms of a simple idea that we call the base-drift hypothesis. This hypothesis correlates the deviations from the stationarity of the Markov process to the evolutionary distanced _AB ^(P) of two species A and B, relative to the processP. We conclude by discussing the implications of our findings for future work.     

Analysis of ancient sequence motifs in the H-PPase family

The unique family of membrane-bound proton-pumping inorganic pyrophosphatases, involving pyrophosphate as the alternative to ATP, was investigated by characterizing 166 members of the UniProtKB/Swiss-Prot + UniProtKB/TrEMBL databases and available completed genomes, using sequence comparisons and a hidden Markov model based upon a conserved 57-residue region in the loop between transmembrane segments 5 and 6. The hidden Markov model was also used to search the approximately one million sequences recently reported from a large-scale sequencing project of organisms in the Sargasso Sea, resulting in additional 164 partial pyrophosphatase sequences. The strongly conserved 57-residue region was found to contain two nonapeptidyl sequences, mainly consisting of the four 'very early' proteinaceous amino acid residues Gly, Ala, Val and Asp, compatible with an ancient origin of the inorganic pyrophosphatases. The nonapeptide patterns have charged amino acid residues at positions 1, 5 and 9, are apparent binding sites for the substrate and parts of the active site, and were shown to be so specific for these enzymes that they can be used for functional assignments of unannotated genomes.     

EST analysis in barley defines a unigene set comprising 4,000 genes

We report the generation of 13,109 EST (Expressed Sequence Tag) sequences from barley as a first step towards the generation of a unigene set for this organism. Sequences were generated from three libraries encompassing 7,568 cDNA clones. Comparisons to nucleic acid and protein sequence databases enabled the assignment of putative functions to the mRNAs. The results of the searches against protein databases were parsed and built into a regularly updated database, available over the World Wide Web. The Stack_Pack clustering system has been applied to survey the level of redundancy, which was calculated to amount to 69%, thus we identified 4,000 different barley genes. To prove the usability of the results of the clustering process for further experiments, we subjected alignments with sequences similar to elongation factor 1 alpha to additional analysis. These sequences represented the largest group with identical putative functions (228 members) and clustering based on the analysis of 3′ sequences subdivided the group into five different assemblies. Alignments of the consensus sequences facilitated the development of PCR assays suitable for genetic mapping of four of the different gene-family members, which reside on chromosomes 2H, 4H and 5H, thus demonstrating the suitability of the cluster-results as a basis for in-depth analyses of barley gene families. Received: 15 March 2001 / Accepted: 18 April 2001     

PROPHET--a national computing resource for life science research

PROPHET is a national computing resource tailored to meet the data management and analysis needs of life scientists working in a wide variety of disciplines, ranging from pharmacology to molecular biology. The PROPHET system offers a fully integrated graphics-oriented environment designed for the manipulation and analysis of tabular data, graphs, molecular structures, biological simulation models, and protein and nucleic acid sequences, and it includes access to molecular structure and sequence databases.     

Personal access to sequence databases on personal computers.

A comprehensive package of software has been developed to access nucleic acid and protein sequence databases on stand-alone IBM personal computers. The software combines keyword search on the annotation fields of the data with pattern matching algorithms on the biological sequences. Sequences containing complex sites like promoters or kink sites can be identified as well as sequences that are similar to a query sequence. Protein sequences with particular patterns of amino acids such as hydrophobic regions can be identified as well. Considering the relatively inexpensive hard disks now available, personal computers have become a cost-effective alternative to mainframe processing for sequence databases.