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Biomedical subjects

S Liuni

Publications and source records attributed to S Liuni.

29 records · Page 2Linked to original sources
PubMed1997

Structural and compositional features of untranslated regions of eukaryotic mRNAs.

The important role of 5' and 3' untranslated regions of eukaryotic mRNAs in gene regulation and expression is now widely accepted. In order to study the general structural and compositional features of these sequences we developed UTRdb, a specialized database of 5' and 3'-UTR sequences from seven different taxonomic groups of eukaryotic mRNAs cleaned of redundancy. The analysis of the UTR sequences contained in this database showed that 5'-UTR sequences, on average 200 nucleotides long, are 1.5-3 times shorter than the corresponding 3'-UTR sequences in the various taxonomic groups considered here. As to their compositional properties on average 5'-UTR sequences resulted in all cases GC richer than 3'-UTR sequences, and significant correlations were found between the GC content of 5' and 3'-UTR sequences and the GC content of the third silent codon positions of the corresponding protein coding genes. The dinucleotide analysis showed a differential depletion of CpG in vertebrate 5' and 3'-UTR, with 5'-UTR sequences being more CpG-rich, and a generalized depletion of TpA in both 5' and 3'-UTR was observed in all eukaryotic sequence collections.

Base Composition↗
PubMed1996

Databases of mRNA untranslated regions for metazoa.

The important role that untranslated regions of mRNAs (UTR) may play in gene regulation and expression is now widely accepted. For this reason we developed UTRDB, a specialized database of 5'- and 3'-UTR of eukaryotic mRNAs cleaned of redundancy. This paper describes the composition and the general feature of UTRDB. The analysis of UTRDB by using suitable statistical methods could provide useful information for guiding the experimental work aimed at delucidating the role of UTR sequences in gene regulation and expression.

Algorithms↗
PubMed1996

CLEANUP: a fast computer program for removing redundancies from nucleotide sequence databases.

A key concept in comparing sequence collections is the issue of redundancy. The production of sequence collections free from redundancy is undoubtedly very useful, both in performing statistical analyses and accelerating extensive database searching on nucleotide sequences. Indeed, publicly available databases contain multiple entries of identical or almost identical sequences. Performing statistical analysis on such biased data makes the risk of assigning high significance to non-significant patterns very high. In order to carry out unbiased statistical analysis as well as more efficient database searching it is thus necessary to analyse sequence data that have been purged of redundancy. Given that a unambiguous definition of redundancy is impracticable for biological sequence data, in the present program a quantitative description of redundancy will be used, based on the measure of sequence similarity. A sequence is considered redundant if it shows a degree of similarity and overlapping with a longer sequence in the database greater than a threshold fixed by the user. In this paper we present a new algorithm based on an "approximate string matching' procedure, which is able to determine the overall degree of similarity between each pair of sequences contained in a nucleotide sequence database and to generate automatically nucleotide sequence collections free from redundancies.

Algorithms↗
PubMed1993

FASTPAT: a fast and efficient algorithm for string searching in DNA sequences.

A new string searching algorithm is presented aimed at searching for the occurrence of character patterns in longer character texts. The algorithm, specifically designed for nucleic acid sequence data, is essentially derived from the Boyer-Moore method (Comm. ACM, 20, 762-772, 1977). Both pattern and text data are compressed so that the natural 4-letter alphabet of nucleic acid sequences is considerably enlarged. The string search starts from the last character of the pattern and proceeds in large jumps through the text to be searched. The data compression and searching algorithm allows one to avoid searching for patterns not present in the text as well as to inspect, for each pattern, all text characters until the exact match with the text is found. These considerations are supported by empirical evidence and comparisons with other methods.

Algorithms↗
PubMed1993

SIMD parallelization of the WORDUP algorithm for detecting statistically significant patterns in DNA sequences.

The development of new techniques in sequencing nuclei acids has produced a great amount of sequence data and has led to the discovery of new relationships. In this paper, we study a method for parallelizing the algorithm WORDUP, which detects the presence of statistically significant patterns in DNA sequences. WORDUP implements an efficient method to identify the presence of statistically significant oligomers in a non-homologous group of sequences. It is based on a modified version of the Boyer-Moore algorithm, which is one of the fastest algorithms for string matching available in the literature. The aim of the parallel version of WORDUP presented here is to speed up the computational time and allow the analysis of a greater set of longer nucleotide sequences, which is usually impractical with sequential algorithms.

Algorithms↗
PubMed1992

WORDUP: an efficient algorithm for discovering statistically significant patterns in DNA sequences.

We present here a fast and sensitive method designed to isolate short nucleotide sequences which have non-random statistical properties and may thus be biologically active. It is based on a first order Markov analysis and allows us to detect statistically significant sequence motifs from six to ten nucleotides long which are significantly shared (or avoided) in the sequences under investigation. This method has been tested on a set of 521 sequences extracted from the Eukaryotic Promoter Database (2). Our results demonstrate the accuracy and the efficiency of the method in that the sequence motifs which are known to act as eukaryotic promoters, such as the TATA-box and the CAAT-box, were clearly identified. In addition we have found other statistically significant motifs, the biological roles of which are yet to be clarified.

Algorithms↗
PubMed1992

A simple method for global sequence comparison.

A simple method of sequence comparison, based on a correlation analysis of oligonucleotide frequency distributions, is here shown to be a reliable test of overall sequence similarity. The method does not involve sequence alignment procedures and permits the rapid screening of large amounts of sequence data. It identifies those sequences which deserve more careful analysis of sequence similarity at the level of resolution of the single nucleotide. It uses observed quantities only and does not involve the adoption of any theoretical model.

Algorithms↗
PubMed1990

Detection of latent sequence periodicities.

A method is proposed for the automatic detection of serial periodicities in a linear sequence. Its application to DNA subtelomeric sequences from two lower eukaryotes, P.falciparum and S.cerevisiae, reveals ordered patterns organised in hierarchical periodicities, not easily recognizable by other methods. The possible implications concerning the evolution of tandemly repetitive arrays are discussed in light of a model which involves, as successive steps, random repeat modification, the fusion of differently modified repeat versions into longer units, and the amplification of (and/or homogenization to) the more recent repeat units.

Algorithms↗
PubMed1990

Reorganization and merging of the EMBL and GenBank keyword indexes in a tree structure for more efficient retrieval of nucleic acid sequences.

EMBL and GenBank keyword indexes have no hierarchical structure. In this paper we present a method for merging and reorganizing them in a tree structure whose primary roots are the keywords 'protein', 'DNA', 'RNA', and 'unclassified'. Synonymous keywords have been grouped together and erroneous keywords have been corrected. This taxonomic organization of keywords results in a more extensive and efficient retrieval which is further aided by "synonyms declaration". The tree has been produced using the computer programs GENPOINT and CREANET.

Abstracting and Indexing↗
PubMed1988

A backtranslation method based on codon usage strategy.

This study describes a method for the backtranslation of an aminoacidic sequence, an extremely useful tool for various experimental approaches. It involves two computer programs CLUSTER and BACKTR written in Fortran 77 running on a VAX/VMS computer. CLUSTER generates a reliable codon usage table through a cluster analysis, based on a chi 2-like distance between the sequences. BACKTR produces backtranslated sequences according to different options when use is made of the codon usage table obtained in addition to selecting the least ambiguous potential oligonucleotide probes within an aminoacidic sequence. The method was tested by applying it to 158 yeast genes.

Amino Acid Sequence↗