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K Albermann

Publications and source records attributed to K Albermann.

12 recordsLinked to original sources
PubMed2001

Functional and structural genomics using PEDANT.

MOTIVATION: Enormous demand for fast and accurate analysis of biological sequences is fuelled by the pace of genome analysis efforts. There is also an acute need in reliable up-to-date genomic databases integrating both functional and structural information. Here we describe the current status of the PEDANT software system for high-throughput analysis of large biological sequence sets and the genome analysis server associated with it. RESULTS: The principal features of PEDANT are: (i) completely automatic processing of data using a wide range of bioinformatics methods, (ii) manual refinement of annotation, (iii) automatic and manual assignment of gene products to a number of functional and structural categories, (iv) extensive hyperlinked protein reports, and (v) advanced DNA and protein viewers. The system is easily extensible and allows to include custom methods, databases, and categories with minimal or no programming effort. PEDANT is actively used as a collaborative environment to support several on-going genome sequencing projects. The main purpose of the PEDANT genome database is to quickly disseminate well-organized information on completely sequenced and unfinished genomes. It currently includes 80 genomic sequences and in many cases serves as the only source of exhaustive information on a given genome. The database also acts as a vehicle for a number of research projects in bioinformatics. Using SQL queries, it is possible to correlate a large variety of pre-computed properties of gene products encoded in complete genomes with each other and compare them with data sets of special scientific interest. In particular, the availability of structural predictions for over 300 000 genomic proteins makes PEDANT the most extensive structural genomics resource available on the web.

Arabidopsis↗
PubMed2000

Integrative analysis of protein interaction data.

We have developed a method for the integrative analysis of protein interaction data. It comprises clustering, visualization and data integration components. The method is generally applicable for all sequenced organisms. Here, we describe in detail the combination of protein interaction data in the yeast Saccharomyces cerevisiae with the functional classification of all yeast proteins. We evaluate the utility of the method by comparison with experimental data and deduce hypotheses about the functional role of so far uncharacterized proteins. Further applications of the integrative analysis method are discussed. The method presented here is powerful and flexible. We show that it is capable of mining large-scale data sets.

Animals↗
PubMed1999

Dynamics of gene expression revealed by comparison of serial analysis of gene expression transcript profiles from yeast grown on two different carbon sources.

We describe a genome-wide characterization of mRNA transcript levels in yeast grown on the fatty acid oleate, determined using Serial Analysis of Gene Expression (SAGE). Comparison of this SAGE library with that reported for glucose grown cells revealed the dramatic adaptive response of yeast to a change in carbon source. A major fraction (>20%) of the 15,000 mRNA molecules in a yeast cell comprised differentially expressed transcripts, which were derived from only 2% of the total number of approximately 6300 yeast genes. Most of the mRNAs that were differentially expressed code for enzymes or for other proteins participating in metabolism (e.g., metabolite transporters). In oleate-grown cells, this was exemplified by the huge increase of mRNAs encoding the peroxisomal beta-oxidation enzymes required for degradation of fatty acids. The data provide evidence for the existence of redox shuttles across organellar membranes that involve peroxisomal, cytoplasmic, and mitochondrial enzymes. We also analyzed the mRNA profile of a mutant strain with deletions of the PIP2 and OAF1 genes, encoding transcription factors required for induction of genes encoding peroxisomal proteins. Induction of genes under the immediate control of these factors was abolished; other genes were up-regulated, indicating an adaptive response to the changed metabolism imposed by the genetic impairment. We describe a statistical method for analysis of data obtained by SAGE.

Carbon↗
PubMed1997

Overview of the yeast genome.

The collaboration of more than 600 scientists from over 100 laboratories to sequence the Saccharomyces cerevisiae genome was the largest decentralised experiment in modern molecular biology and resulted in a unique data resource representing the first complete set of genes from a eukaryotic organism. 12 million bases were sequenced in a truly international effort involving European, US, Canadian and Japanese laboratories. While the yeast genome represents only a small fraction of the information in today's public sequence databases, the complete, ordered and non-redundant sequence provides an invaluable resource for the detailed analysis of cellular gene function and genome architecture. In terms of throughput, completeness and information content, yeast has always been the lead eukaryotic organism in genomics; it is still the largest genome to be completely sequenced.

Chromosome Mapping↗
PubMed1997

The nucleotide sequence of Saccharomyces cerevisiae chromosome VII.

The complete nucleotide sequence of Saccharomyces cerevisiae chromosome VII has 572 predicted open reading frames (ORFs), of which 341 are new. No correlation was found between G+C content and gene density along the chromosome, and their variations are random. Of the ORFs, 17% show high similarity to human proteins. Almost half of the ORFs could be classified in functional categories, and there is a slight increase in the number of transcription (7.0%) and translation (5.2%) factors when compared with the complete S. cerevisiae genome. Accurate verification procedures demonstrate that there are less than two errors per 10,000 base pairs in the published sequence.

Base Sequence↗
PubMed1997

The nucleotide sequence of Saccharomyces cerevisiae chromosome XII.

The yeast Saccharomyces cerevisiae is the pre-eminent organism for the study of basic functions of eukaryotic cells. All of the genes of this simple eukaryotic cell have recently been revealed by an international collaborative effort to determine the complete DNA sequence of its nuclear genome. Here we describe some of the features of chromosome XII.

Base Sequence↗
PubMed1997

The nucleotide sequence of Saccharomyces cerevisiae chromosome XIV and its evolutionary implications.

In 1992 we started assembling an ordered library of cosmid clones from chromosome XIV of the yeast Saccharomyces cerevisiae. At that time, only 49 genes were known to be located on this chromosome and we estimated that 80% to 90% of its genes were yet to be discovered. In 1993, a team of 20 European laboratories began the systematic sequence analysis of chromosome XIV. The completed and intensively checked final sequence of 784,328 base pairs was released in April, 1996. Substantial parts had been published before or had previously been made available on request. The sequence contained 419 known or presumptive protein-coding genes, including two pseudogenes and three retrotransposons, 14 tRNA genes, and three small nuclear RNA genes. For 116 (30%) protein-coding sequences, one or more structural homologues were identified elsewhere in the yeast genome. Half of them belong to duplicated groups of 6-14 loosely linked genes, in most cases with conserved gene order and orientation (relaxed interchromosomal synteny). We have considered the possible evolutionary origins of this unexpected feature of yeast genome organization.

Base Sequence↗
PubMed1997

The nucleotide sequence of Saccharomyces cerevisiae chromosome XV.

Chromosome XV was one of the last two chromosomes of Saccharomyces cerevisiae to be discovered. It is the third-largest yeast chromosome after chromosomes XII and IV, and is very similar in size to chromosome VII. It alone represents 9% of the yeast genome (8% if ribosomal DNA is included). When systematic sequencing of chromosome XV was started, 93 genes or markers were identified, and most of them were mapped. However, very little else was known about chromosome XV which, in contrast to shorter chromosomes, had not been the object of comprehensive genetic or molecular analysis. It was therefore decided to start sequencing chromosome XV only in the third phase of the European Yeast Genome Sequencing Programme, after experience was gained on chromosomes III, XI and II. The sequence of chromosome XV has been determined from a set of partly overlapping cosmid clones derived from a unique yeast strain, and physically mapped at 3.3-kilobase resolution before sequencing. As well as numerous new open reading frames (ORFs) and genes encoding tRNA or small RNA molecules, the sequence of 1,091,283 base pairs confirms the high proportion of orphan genes and reveals a number of ancestral and successive duplications with other yeast chromosomes.

Base Sequence↗
PubMed1997

The nucleotide sequence of Saccharomyces cerevisiae chromosome XVI.

The nucleotide sequence of the 948,061 base pairs of chromosome XVI has been determined, completing the sequence of the yeast genome. Chromosome XVI was the last yeast chromosome identified, and some of the genes mapped early to it, such as GAL4, PEP4 and RAD1 (ref. 2) have played important roles in the development of yeast biology. The architecture of this final chromosome seems to be typical of the large yeast chromosomes, and shows large duplications with other yeast chromosomes. Chromosome XVI contains 487 potential protein-encoding genes, 17 tRNA genes and two small nuclear RNA genes; 27% of the genes have significant similarities to human gene products, and 48% are new and of unknown biological function. Systematic efforts to explore gene function have begun.

Base Sequence↗
PubMed1997

MIPS: a database for protein sequences, homology data and yeast genome information.

The MIPS group (Martinsried Institute for Protein Sequences) at the Max-Planck-Institute for Biochemistry, Martinsried near Munich, Germany, collects, processes and distributes protein sequence data within the framework of the tripartite association of the PIR-International Protein Sequence Database (,). MIPS contributes nearly 50% of the data input to the PIR-International Protein Sequence Database. The database is distributed on CD-ROM together with PATCHX, an exhaustive supplement of unique, unverified protein sequences from external sources compiled by MIPS. Through its WWW server (http://www.mips.biochem.mpg.de/ ) MIPS permits internet access to sequence databases, homology data and to yeast genome information. (i) Sequence similarity results from the FASTA program () are stored in the FASTA database for all proteins from PIR-International and PATCHX. The database is dynamically maintained and permits instant access to FASTA results. (ii) Starting with FASTA database queries, proteins have been classified into families and superfamilies (PROT-FAM). (iii) The HPT (hashed position tree) data structure () developed at MIPS is a new approach for rapid sequence and pattern searching. (iv) MIPS provides access to the sequence and annotation of the complete yeast genome (), the functional classification of yeast genes (FunCat) and its graphical display, the 'Genome Browser' (). A CD-ROM based on the JAVA programming language providing dynamic interactive access to the yeast genome and the related protein sequences has been compiled and is available on request.

Academies and Institutes↗
PubMed1992

Nuclear factor kappa B: an oxidative stress-responsive transcription factor of eukaryotic cells (a review).

NF-kappa B is a multiprotein complex that can activate a great variety of genes involved in early defence reactions of higher organisms. In nonstimulated cells, NF-kappa B resides in the cytoplasm in an inactive complex with the inhibitor I kappa B. Pathogenic stimuli cause release of I kappa B and allow NF-kappa B to enter the nucleus, bind to DNA control elements and, thereby, induce the synthesis of mRNA. A puzzling feature of NF-kappa B is that its activation is triggered by a great variety of agents. These include the cytokines interleukin-1 and tumor necrosis factor, viruses, double-stranded RNA, endotoxins, phorbol esters, UV light and ionizing radiation. We recently found that also low concentrations of H2O2 activate NF-kappa B and that various antioxidants prevent the induction by H2O2. Subsequent analysis revealed that antioxidants not only suppress the activation of NF-kappa B by H2O2 but by all other inducers tested so far. In this review, we will discuss the evidences that NF-kappa B is an oxidative stress-responsive transcription factor of higher eukaryotic cells.

Animals↗