Biomedical subjects

L J Heyer

Publications and source records attributed to L J Heyer.

5 recordsLinked to original sources

PubMed2005

MAGIC Tool: integrated microarray data analysis.

SUMMARY: Several programs are now available for analyzing the large datasets arising from cDNA microarray experiments. Most programs are expensive commercial packages or require expensive third party software. Some are freely available to academic researchers, but are limited to one operating system. MicroArray Genome Imaging and Clustering Tool (MAGIC Tool) is an open source program that works on all major platforms, and takes users 'from tiff to gif'. Several unique features of MAGIC Tool are particularly useful for research and teaching. AVAILABILITY: http://www.bio.davidson.edu/MAGIC

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PubMed1999

Exploring expression data: identification and analysis of coexpressed genes.

Analysis procedures are needed to extract useful information from the large amount of gene expression data that is becoming available. This work describes a set of analytical tools and their application to yeast cell cycle data. The components of our approach are (1) a similarity measure that reduces the number of false positives, (2) a new clustering algorithm designed specifically for grouping gene expression patterns, and (3) an interactive graphical cluster analysis tool that allows user feedback and validation. We use the clusters generated by our algorithm to summarize genome-wide expression and to initiate supervised clustering of genes into biologically meaningful groups.

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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.

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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.

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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.

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