Search PubMed⌕ Search

Biomedical subjects

G D Stormo

Publications and source records attributed to G D Stormo.

At least 37 records · Page 2Linked to original sources
PubMed1998

Specificity, free energy and information content in protein-DNA interactions.

Site-specific DNA-protein interactions can be studied using experimental and computational methods. Experimental approaches typically analyze a protein-DNA interaction by measuring the free energy of binding under a variety of conditions. Computational methods focus on alignments of known binding sites for a protein, and, from these alignments, make estimates of the binding energy. Understanding the relationship between these two perspectives, and finding ways to improve both, is a major challenge of modern molecular biology.

Binding Sites↗
PubMed1998

Xlandscape: the graphical display of word frequencies in sequences.

MOTIVATION: To provide a graphical interface for the generation, display and manipulation of a sequence landscape that will run on all X-windows-based Unix workstations. RESULTS: The sequence landscape approach enables the representation of the frequency of occurrence of all query sequence sub-words within a database. The landscape approach can detect tandem and other repeating word motifs, specific sub-words that are over-represented words in a particular database using Markov probability and the preference for sub-words belonging to either one of two databases. All these features aid in the classification of a query sequence. Given the open-text format for sequences and databases, the Xlandscape tool can be applied to a wide range of problems.

Algorithms↗
PubMed1998

An RNA folding method capable of identifying pseudoknots and base triples.

MOTIVATION: Recently, we described a Maximum Weighted Matching (MWM) method for RNA structure prediction. The MWM method is capable of detecting pseudoknots and other tertiary base-pairing interactions in a computationally efficient manner (Cary and Stormo, Proceedings of the Third International Conference on Intelligent Systems for Molecular Biology, pp. 75-80, 1995). Here we report on the results of our efforts to improve the MWM method's predictive accuracy, and show how the method can be extended to detect base interactions formerly inaccessible to automated RNA modeling techniques. RESULTS: Improved performance in MWM structure prediction was achieved in two ways. First, new ways of calculating base pair likelihoods have been developed. These allow experimental data and combined statistical and thermodynamic information to be used by the program. Second, accuracy was improved by developing techniques for filtering out spurious base pairs predicted by the MWM program. We also demonstrate here a means by which the MWM folding method may be used to detect the presence of base triples in RNAs. AVAILABILITY: http://www.cshl.org/mzhanglab/tabaska/j axpage. html CONTACT: tabaska@cshl.org

Algorithms↗
PubMed1997

Finding the most significant common sequence and structure motifs in a set of RNA sequences.

We present a computational scheme to locally align a collection of RNA sequences using sequence and structure constraints. In addition, the method searches for the resulting alignments with the most significant common motifs, among all possible collections. The first part utilizes a simplified version of the Sankoff algorithm for simultaneous folding and alignment of RNA sequences, but maintains tractability by constructing multi-sequence alignments from pairwise comparisons. The algorithm finds the multiple alignments using a greedy approach and has similarities to both CLUSTAL and CONSENSUS, but the core algorithm assures that the pairwise alignments are optimized for both sequence and structure conservation. The choice of scoring system and the method of progressively constructing the final solution are important considerations that are discussed. Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones.

Algorithms↗
PubMed1997

Quantitative specificity of the Mnt repressor.

The Mnt protein of Salmonella phage P22 binds site-specifically to its operator. To better understand this binding we used dideoxy DNA sequencing in a quantitative manner to determine the relative binding constants, and hence the relative free energies, of wild-type Mnt protein to a substantial number of variants of its operator. These measurements were supported by experiments which used the SELEX procedure to generate a set of operators from an initially randomized population. In the Discussion we show that the present model of Mnt protein/operator binding, due to Sauer and co-workers, along with the assumption of an independent contribution of each position in the operator to the total binding, provides a reasonably accurate description of the system. We also discuss the use of information content as a measure of DNA-protein binding specificity with the Mnt protein/operator system serving as an example and show again that the assumption of independence supports the current view of this case of site-specific binding.

Bacteriophage P22↗
PubMed1997

PromFD 1.0: a computer program that predicts eukaryotic pol II promoters using strings and IMD matrices.

MOTIVATION: A large number of new DNA sequences with virtually unknown functions are generated as the Human Genome Project progresses. Therefore, it is essential to develop computer algorithms that can predict the functionality of DNA segments according to their primary sequences, including algorithms that can predict promoters. Although several promoter-predicting algorithms are available, they have high false-positive detections and the rate of promoter detection needs to be improved further. RESULTS: In this research, PromFD, a computer program to recognize vertebrate RNA polymerase II promoters, has been developed. Both vertebrate promoters and non-promoter sequences are used in the analysis. The promoters are obtained from the Eukaryotic Promoter Database. Promoters are divided into a training set and a test set. Non-promoter sequences are obtained from the GenBank sequence databank, and are also divided into a training set and a test set. The first step is to search out, among all possible permutations, patterns of strings 5-10 bp long, that are significantly over-represented in the promoter set. The program also searches IMD (Information Matrix Database) matrices that have a significantly higher presence in the promoter set. The results of the searches are stored in the PromFD database, and the program PromFD scores input DNA sequences according to their content of the database entries. PromFD predicts promoters-their locations and the location of potential TATA boxes, if found. The program can detect 71% of promoters in the training set with a false-positive rate of under 1 in every 13,000 bp, and 47% of promoters in the test set with a false-positive rate of under 1 in every 9800 bp. PromFD uses a new approach and its false-positive identification rate is better compared with other available promoter recognition algorithms. The source code for PromFD is in the 'c+2' language.

Algorithms↗
PubMed1997

Displaying the information contents of structural RNA alignments: the structure logos.

MOTIVATION: We extend the standard 'Sequence Logo' method of Schneider and Stevens (Nucleic Acids Res., 18, 6097-6100, 1990) to incorporate prior frequencies on the bases, allow for gaps in the alignments, and indicate the mutual information of base-paired regions in RNA. RESULTS: Given an alignment of RNA sequences with the base pairings indicated, the program will calculate the information at each position, including the mutual information of the base pairs, and display the results in a 'Structure Logo'. Alignments without base pairing can also be displayed in a 'Sequence Logo', but still allowing gaps and incorporating prior frequencies if desired. AVAILABILITY: The code is available from, and an Internet server can be used to run the program at, http://www.cbs.dtu.dk/gorodkin/appl/slogo. html.

Algorithms↗
PubMed1997

Finding common sequence and structure motifs in a set of RNA sequences.

We present a computational scheme to search for the most common motif, composed of a combination of sequence and structure constraints, among a collection of RNA sequences. The method uses a simplified version of the Sankoff algorithm for simultaneous folding and alignment of RNA sequences, but maintains tractability by constructing multi-sequence alignments from pairwise comparisons. The overall method has similarities to both CLUSTAL and CONSENSUS, but the core algorithm assures that the pairwise alignments are optimized for both sequence and structure conservation. Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones.

Algorithms↗
PubMed1997

Automated alignment of RNA sequences to pseudoknotted structures.

Seq7 is a new program for generating multiple structure-based alignments of RNA sequences. By using a variant of Dijkstra's algorithm to find the shortest path through a specially constructed graph, Seq7 is able to align RNA sequences to pseudoknotted structures in polynomial time. In this paper, we describe the operation of Seq7 and demonstrate the program's abilities. We also describe the use of Seq7 in an Expectation-Maximization procedure that automates the process of structural modeling and alignment of RNA sequences.

Algorithms↗
PubMed1995

Multi-alphabet consensus algorithm for identification of low specificity protein-DNA interactions.

A method for the identification and characterization of protein-DNA interactions is presented. We have developed an approach for finding unknown multiple patterns that occur imperfectly in a set of several sequences. The pattern may contain letters from the nucleotide alphabet (A, C, G and T) including ambiguous characters (A/C, A/G, A/T; A/C/G, etc.). This method reveals weak DNA signals on an unaligned set of DNA fragments known to be functionally related and assumes no prior information on the sequences' alignment. It determines the locations of the signals from only the information intrinsic to the sequences themselves. We have applied this method to analyze the binding sites of cAMP receptor protein (CRP). The consensus based on these data are discussed and a comparison of the consensus with the crystal structure of CAP-DNA complex is presented. We further show that in a mixture of DNA sequences, containing binding sites for two different proteins, both classes of binding sites can be discovered simultaneously by this method. The DNA sequences of nucleosome cores from chicken erythrocyte and a set of the other known nucleosomal sequences show existence of symmetrical features in nucleosome-binding DNA sequences. We also show multi-alphabet patterns that can play a role in the phasing signal on the nucleosome DNA molecule and have compared the results with existing models of nucleosome positioning.

Algorithms↗
PubMed1995

Identification of protein coding regions in genomic DNA.

We have developed a computer program, GeneParser, which identifies and determines the fine structure of protein genes in genomic DNA sequences. The program scores all subintervals in a sequence for content statistics indicative of introns and exons, and for sites that identify their boundaries. This information is weighted by a neural network to approximate the log-likelihood that each subinterval exactly represents an intron or exon (first, internal or last). A dynamic programming algorithm is then applied to this data to find the combination of introns and exons that maximizes the likelihood function. Using this method, we can rapidly generate ranked suboptimal solutions, each of which is the optimum solution containing a given intron-exon junction. We have tested the system on a large collection of human genes. On sequences not used in training, we achieved a correlation coefficient for exon nucleotide prediction of 0.89. For a subset of G + C-rich genes, a correlation coefficient of 0.94 was achieved. We have also quantified the robustness of the method to substitution and frame-shift errors and show how the system can be optimized for performance on sequences with known levels of sequencing errors.

Base Composition↗
PubMed1995

MATRIX SEARCH 1.0: a computer program that scans DNA sequences for transcriptional elements using a database of weight matrices.

The information matrix database (IMD), a database of weight matrices of transcription factor binding sites, is developed. MATRIX SEARCH, a program which can find potential transcription factor binding sites in DNA sequences using the IMD database, is also developed and accompanies the IMD database. MATRIX SEARCH adopts a user interface very similar to that of the SIGNAL SCAN program. MATRIX SEARCH allows the user to search an input sequence with the IMD automatically, to visualize the matrix representations of sites for particular factors, and to retrieve journal citations. The source code for MATRIX SEARCH is in the 'C' language, and the program is available for unix platforms.

Base Sequence↗
PubMed1995

A consensus sequence for binding of Lrp to DNA.

Lrp (leucine-responsive regulatory protein) is a major regulatory protein involved in the expression of numerous operons in Escherichia coli. For ilvIH, one of the operons positively regulated by Lrp, Lrp binds to multiple sites upstream of the transcriptional start site and activates transcription. An alignment of 12 Lrp binding sites within ilvIH DNA from two different organisms revealed a tentative consensus sequence AGAAT TTTATTCT (Q. Wang, M. Sacco, E. Ricca, C.T. Lago, M. DeFelice, and J.M. Calvo, Mol. Microbiol. 7:883-891, 1993). To further characterize the binding specificity of Lrp, we used a variation of the Selex procedure of C. Tuerk and L. Gold (Science 249:505-510, 1990) to identify sequences that bound Lrp out of a pool of 10(12) different DNA molecules. We identified 63 related DNA sequences that bound Lrp and estimated their relative binding affinities for Lrp. A consensus sequence derived from analysis of these sequences, YAGHAWATTWT DCTR, where Y = C or T, H = not G, W = A or T, D = not C, and R = A or G, contains clear dyad symmetry and is very similar to the one defined earlier. To test the idea that Lrp in the presence of leucine might bind to a different subset of DNA sequences, we carried out a second selection experiment with leucine present during the binding reactions. DNA sequences selected in the presence or absence of leucine were similar, and leucine did not stimulate binding to any of the sequences that were selected in the presence of leucine. Therefore, it is unlikely that leucine changes the specificity of Lrp binding.

Bacterial Proteins↗
PubMed1995

Graph-theoretic approach to RNA modeling using comparative data.

We have examined the utility of a graph-theoretic algorithm for building comparative RNA models. The method uses a maximum weighted matching algorithm to find the optimal set of basepairs given the mutual information for all pairs of alignment positions. In all cases examined, the technique generated models similar to those based on conventional comparative analysis. Any set of pairwise interactions can be suggested including pseudoknots. Here we describe the details of the method and demonstrate its implementation on tRNA where many secondary and tertiary base-pairs are accurately predicted. We also examine the usefulness of the method for the identification of shared structural features in families of RNAs isolated by artificial selection methods such as SELEX.

Algorithms↗
PubMed1994

Quantitative analysis of ribosome binding sites in E.coli.

185 clones with randomized ribosome binding sites, from position -11 to 0 preceding the coding region of beta-galactosidase, were selected and sequenced. The translational yield of each clone was determined; they varied by more than 3000-fold. Multiple linear regression analysis was used to determine the contribution to translation initiation activity of each base at each position. Features known to be important for translation initiation, such as the initiation codon, the Shine/Dalgarno sequence, the identity of the base at position -3 and the occurrence of alternative ATGs, are all found to be important quantitatively for activity. No other features are found to be of general significance, although the effects of secondary structure can be seen as outliers. A comparison to a large number of natural E.coli translation initiation sites shows the information profile to be qualitatively similar although differing quantitatively. This is probably due to the selection for good translation initiation sites in the natural set compared to the low average activity of the randomized set.

Base Sequence↗
PubMed1994

Detection of deletions in the mitochondrial genome of Caenorhabditis elegans.

We have examined an aging population of Caenorhabditis elegans via a PCR assay to determine if deletions in the mitochondrial genome occur in the nematode. We detected eight such deletions, identified the breakpoints of four of these, and discovered direct repeats of 4-8 base pairs at the site of all four deletions. Six of the eight repeats involved in the deletions are located in or immediately adjacent to tRNAs. Without a biochemical bias, the probability of direct repeats being present at all four breakpoints was 4 x 10(-6).

Aging↗
PubMed1994

Quantitative DNA sequencing to determine the relative protein-DNA binding constants to multiple DNA sequences.

DNA sequencing technology was modified into a quantitative assay, which for multiple DNA sequences allowed the simultaneous determination of relative protein-DNA binding constants. The band mobility shift of the protein-DNA binding reactions partitions the mixture of DNA sequences into bound and unbound fractions. The quantitation of that partitioning gives directly the relative binding constants, usually with accuracies of better than +/- 20%. The protein of interest was the Mnt repressor of Salmonella bacteriophage P22, and the synthetic DNA contained Mnt's natural operator with a randomized position.

Adenosine Triphosphate↗