Biomedical subjects

Esko Ukkonen

Publications and source records attributed to Esko Ukkonen.

6 recordsLinked to original sources

PubMed2006

Planning optimal measurements of isotopomer distributions for estimation of metabolic fluxes.

MOTIVATION: Flux estimation using isotopomer information of metabolites is currently the most reliable method to obtain quantitative estimates of the activity of metabolic pathways. However, the development of isotopomer measurement techniques for intermediate metabolites is a demanding task. Careful planning of isotopomer measurements is thus needed to maximize the available flux information while minimizing the experimental effort. RESULTS: In this paper we study the question of finding the smallest subset of metabolites to measure that ensure the same level of isotopomer information as the measurement of every metabolite in the metabolic network. We study the computational complexity of this optimization problem in the case of the so-called positional enrichment data, give methods for obtaining exact and fast approximate solutions, and evaluate empirically the efficacy of the proposed methods by analyzing a metabolic network that models the central carbon metabolism of Saccharomyces cerevisiae.

Algorithms↗

PubMed2006

Genome-wide prediction of mammalian enhancers based on analysis of transcription-factor binding affinity.

Understanding the regulation of human gene expression requires knowledge of the "second genetic code," which consists of the binding specificities of transcription factors (TFs) and the combinatorial code by which TF binding sites are assembled to form tissue-specific enhancer elements. Using a novel high-throughput method, we determined the DNA binding specificities of GLIs 1-3, Tcf4, and c-Ets1, which mediate transcriptional responses to the Hedgehog (Hh), Wnt, and Ras/MAPK signaling pathways. To identify mammalian enhancer elements regulated by these pathways on a genomic scale, we developed a computational tool, enhancer element locator (EEL). We show that EEL can be used to identify Hh and Wnt target genes and to predict activated TFs based on changes in gene expression. Predictions validated in transgenic mouse embryos revealed the presence of multiple tissue-specific enhancers in mouse c-Myc and N-Myc genes, which has implications for organ-specific growth control and tumor-type specificity of oncogenes.

Amino Acid Sequence↗

PubMed2005

Optimization of cDNA-AFLP experiments using genomic sequence data.

MOTIVATION: cDNA amplified fragment length polymorphism (cDNA-AFLP) is one of the few genome-wide level expression profiling methods capable of finding genes that have not yet been cloned or even predicted from sequence but have interesting expression patterns under the studied conditions. In cDNA-AFLP, a complex cDNA mixture is divided into small subsets using restriction enzymes and selective PCR. A large cDNA-AFLP experiment can require a substantial amount of resources, such as hundreds of PCR amplifications and gel electrophoresis runs, followed by manual cutting of a large number of bands from the gels. Our aim was to test whether this workload can be reduced by rational design of the experiment. RESULTS: We used the available genomic sequence information to optimize cDNA-AFLP experiments beforehand so that as many transcripts as possible could be profiled with a given amount of resources. Optimization of the selection of both restriction enzymes and selective primers for cDNA-AFLP experiments has not been performed previously. The in silico tests performed suggest that substantial amounts of resources can be saved by the optimization of cDNA-AFLP experiments.

Algorithms↗

PubMed2003

From gene networks to gene function.

We propose a novel method to identify functionally related genes based on comparisons of neighborhoods in gene networks. This method does not rely on gene sequence or protein structure homologies, and it can be applied to any organism and a wide variety of experimental data sets. The character of the predicted gene relationships depends on the underlying networks;they concern biological processes rather than the molecular function. We used the method to analyze gene networks derived from genome-wide chromatin immunoprecipitation experiments, a large-scale gene deletion study, and from the genomic positions of consensus binding sites for transcription factors of the yeast Saccharomyces cerevisiae. We identified 816 functional relationships between 159 genes and show that these relationships correspond to protein-protein interactions, co-occurrence in the same protein complexes, and/or co-occurrence in abstracts of scientific articles. Our results suggest functions for seven previously uncharacterized yeast genes: KIN3 and YMR269W may be involved in biological processes related to cell growth and/or maintenance, whereas IES6, YEL008W, YEL033W, YHL029C, YMR010W, and YMR031W-A are likely to have metabolic functions.

Computational Biology↗

PubMed2002

Assigning probes into a small number of pools separable by electrophoresis.

MOTIVATION: Measuring transcriptional expression levels (transcriptional profiling) has become one of the most important methods in functional genomics. Still, new measuring methods are needed to obtain more reliable, quantitative data about transcription on a genomic scale. In this paper we concentrate on certain computational optimization problems arising in the design of one such novel method. From a computational point of view the key feature of the new method is that the hybridized probes are distinguished from each other based on their different size. Therefore the probes have to be assigned into pools such that the probes in the same pool have unique sizes different enough from each other. Identification of expressed RNA is given by probe pool and probe size while quantification is given by the label of the probe, e.g. fluorescence intensity. RESULTS: We show how to computationally find the probes and assign them into pools for a whole genome such that (i) each gene has a specific probe suitable for amplification and hybridization, and (ii) the expression level measurement can be done in a minimal number of pools separable by electrophoresis in order to minimize the total experiment cost of the measurement. Our main result is a polynomial-time approximation algorithm for assigning the probes into pools. We demonstrate the feasibility of the procedure by selecting probes for the yeast genome and assigning them into less than 100 pools. The probe sequences and their assignment into pools are available for academic research on request from the authors.

Algorithms↗

PubMed2002

Correlating gene promoters and expression in gene disruption experiments.

MOTIVATION: Finding putative transcription factor binding sites in the upstream sequences of similarly expressed genes has recently become a subject of intensive studies. In this paper we investigate how much gene expression regulation can be attributed to the presence of various binding sites in the gene promoters by correlating the binding sites and the changes in gene expression resulting from gene disruptions (e.g. knockouts). RESULTS: We have developed a data analysis method for comparing mRNA measurements of gene disruption experiments with information about gene promoters. The method was applied to a well-known dataset to uncover correlations between known transcription factor binding site motifs in the upstream regions of all S. cerevisiae genes and the gene expression changes in various gene disruption experiments. The possible explanations of the correlations were categorized and analyzed using e.g. expression cascades. Several correlations turned out to be consistent with existing biological knowledge while some new ones suggest themselves for further study. AVAILABILITY: The resulting tables are available at http://www.cs.helsinki.fi/u/kpalin/CorrDisrupt/.

Algorithms↗