254 research outputs found
Recommended from our members
A fast look-up algorithm for detecting repetitive DNA sequences
We have presented a fast linear time algorithm for recognizing tandem repeats. Our algorithm is a one pass algorithm. No information about the periodicity of tandem repeats is needed. The use of the indices calculated from non-continuous and overlapping {kappa}-tuples allow tandem repeats with insertions and deletions to be recognized
Recommended from our members
A new method for modeling and solving the protein fold recognition problem
Computational recognition of native-like folds from a protein fold database is considered to be a promising alternative approach to the ab initio fold prediction. We present a new and effective method for protein fold recognition through optimally aligning (threading) an amino acid sequence and a protein fold (template). A protein fold, in our database, is represented as a series of core secondary structures, and the alignment quality is determined by three factors. They are (1) the fitness between each amino acid and the environment of its assigned (aligned) template position; (2) pairwise interaction preferences between amino acids that are spatially close; and (3) alignment gap penalties. Our threading algorithm constructs an optimum alignment between an amino acid sequence of size n and a protein fold template of size m in 0((m + n{sup 1+0.5C}-M log(n))n{sup C+1}) time and 0(nm + n{sup C+2}) space, where M is the number of core secondary structures in the fold, and C is a (small) nonnegative integer, determined by a mathematical property of the pairwise interactions in the fold. C is less than or equal to 3 for about 90% of the 296 unique folds in our database, when pairwise interactions are restricted to amino acids 3, when threading requires too much memory and time to be practical on a typical workstation
The complete genomic sequence of 424,015 bp at the centromeric end of the HLA class I region: Gene content and polymorphism
Developing improved MD codes for understanding processive cellulases
"The mechanism of action of cellulose-degrading enzymes is illuminated through a multidisciplinary collaboration that uses molecular dynamics (MD) simulations and expands the capabilities of MD codes to allow simulations of enzymes and substrates on petascale computational facilities. There is a class of glycoside hydrolase enzymes called cellulases that are thought to decrystallize and processively depolymerize cellulose using biochemical processes that are largely not understood. Understanding the mechanisms involved and improving the efficiency of this hydrolysis process through computational models and protein engineering presents a compelling grand challenge. A detailed understanding of cellulose structure, dynamics and enzyme function at the molecular level is required to direct protein engineers to the right modifications or to understand if natural thermodynamic or kinetic limits are in play. Much can be learned about processivity by conducting carefully designed molecular dynamics (MD) simulations of the binding and catalytic domains of cellulases with various substrate configurations, solvation models and thermodynamic protocols. Most of these numerical experiments, however, will require significant modification of existing code and algorithms in order to efficiently use current (terascale) and future (petascale) hardware to the degree of parallelism necessary to simulate a system of the size proposed here. This work will develop MD codes that can efficiently use terascale and petascale systems, not just for simple classical MD simulations, but also for more advanced methods, including umbrella sampling with complex restraints and reaction coordinates, transition path sampling, steered molecular dynamics, and quantum mechanical/molecular mechanical simulations of systems the size of cellulose degrading enzymes acting on cellulose."http://deepblue.lib.umich.edu/bitstream/2027.42/64203/1/jpconf8_125_012049.pd
BESC knowledgebase public portal†
The BioEnergy Science Center (BESC) is undertaking large experimental campaigns to understand the biosynthesis and biodegradation of biomass and to develop biofuel solutions. BESC is generating large volumes of diverse data, including genome sequences, omics data and assay results. The purpose of the BESC Knowledgebase is to serve as a centralized repository for experimentally generated data and to provide an integrated, interactive and user-friendly analysis framework. The Portal makes available tools for visualization, integration and analysis of data either produced by BESC or obtained from external resources
SAND, a New Protein Family: From Nucleic Acid to Protein Structure and Function Prediction
As a result of genome, EST and cDNA sequencing projects, there are huge numbers of
predicted and/or partially characterised protein sequences compared with a relatively small
number of proteins with experimentally determined function and structure. Thus, there is a
considerable attention focused on the accurate prediction of gene function and structure
from sequence by using bioinformatics. In the course of our analysis of genomic sequence
from Fugu rubripes, we identified a novel gene, SAND, with significant sequence identity to
hypothetical proteins predicted in Saccharomyces cerevisiae, Schizosaccharomyces pombe,
Caenorhabditis elegans, a Drosophila melanogaster gene, and mouse and human cDNAs.
Here we identify a further SAND homologue in human and Arabidopsis thaliana by use of
standard computational tools. We describe the genomic organisation of SAND in these
evolutionarily divergent species and identify sequence homologues from EST database
searches confirming the expression of SAND in over 20 different eukaryotes. We confirm
the expression of two different SAND paralogues in mammals and determine expression of
one SAND in other vertebrates and eukaryotes. Furthermore, we predict structural
properties of SAND, and characterise conserved sequence motifs in this protein family
Despite WT1 binding sites in the promoter region of human and mouse nucleoporin glycoprotein 210, WT1 does not influence expression of GP210
BACKGROUND: Glycoprotein 210 (GP210) is a transmembrane component of the nuclear pore complex of metazoans, with a short carboxyterminus protruding towards the cytoplasm. Its function is unknown, but it is considered to be a major structural component of metazoan nuclear pores. Yet, our previous findings showed pronounced differences in expression levels in embryonic mouse tissues and cell lines. In order to identify factors regulating GP210, the genomic organization of human GP210 was analyzed in silico. RESULTS: The human gene was mapped to chromosome 3 and consists of 40 exons spread over 102 kb. The deduced 1887 amino acid showed a high degree of alignment homology to previously reported orthologues. Experimentally we defined two transcription initiation sites, 18 and 29 bp upstream of the ATG start codon. The promoter region is characterized by a CpG island and several consensus binding motifs for gene regulatory transcription factors, including clustered sites associated with Sp1 and the Wilms' tumor suppressor gene zinc finger protein (WT1). In addition, distal to the translation start we found a (GT)n repetitive sequence, an element known for its ability to bind WT1. Homologies for these motifs could be identified in the corresponding mouse genomic region. However, experimental tetracycline dependent induction of WT1 in SAOS osteosarcoma cells did not influence GP210 transcription. CONCLUSION: Although mouse GP210 was identified as an early response gene during induced metanephric kidney development, and WT1 binding sites were identified in the promoter region of the human GP210 gene, experimental modulation of WT1 expression did not influence expression of GP210. Therefore, WT1 is probably not regulating GP210 expression. Instead, we suggest that the identified Sp binding sites are involved
Genome Structure of the Legume, Lotus japonicus
The legume Lotus japonicus has been widely used as a model system to investigate the genetic background of legume-specific phenomena such as symbiotic nitrogen fixation. Here, we report structural features of the L. japonicus genome. The 315.1-Mb sequences determined in this and previous studies correspond to 67% of the genome (472 Mb), and are likely to cover 91.3% of the gene space. Linkage mapping anchored 130-Mb sequences onto the six linkage groups. A total of 10 951 complete and 19 848 partial structures of protein-encoding genes were assigned to the genome. Comparative analysis of these genes revealed the expansion of several functional domains and gene families that are characteristic of L. japonicus. Synteny analysis detected traces of whole-genome duplication and the presence of synteny blocks with other plant genomes to various degrees. This study provides the first opportunity to look into the complex and unique genetic system of legumes
- …