Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of th... more Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We present an algorithm that finds in a family of k permutations of n elements all z common intervals in optimal O(kn+z) time and O(n) additional space. Additionally, we show how to adapt this algorithm to multichromosomal and circular permutations. This extends a result by Uno and Yagiura (Algorithmica 26:290–309, 2000) who present an algorithm to find all z common intervals of k=2 (regular) permutations in optimal O(n+z) time and O(n) space. To achieve our result, we introduce the set of irreducible intervals, a generating subset of the set of all common intervals of k permutations.
Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of th... more Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We present an algorithm that finds in a family of k permutations of n elements all K common intervals in optimal O(nk+K) time and O(n) additional space. This extends a result by Uno and Yagiura (Algorithmica 26, 290-309, 2000) who present an algorithm to find all K common intervals of k = 2 permutations in optimal O(n+K) time and O(n) space. To achieve our result, we introduce the set of irreducible intervals, a generating subset of the set of all common intervals of k permutations.
Comparing gene orders in completely sequenced genomes is a standard approach to locate clusters o... more Comparing gene orders in completely sequenced genomes is a standard approach to locate clusters of functionally associated genes. Often, gene orders are modeled as permutations. Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We consider several problems related to common intervals in multiple genomes. We present an algorithm that finds all common intervals in a family of genomes, each of which might consist of several chromosomes. We present another algorithm that finds all common intervals in a family of circular permutations. A third algorithm finds all common intervals in signed permutations. We also investigate how to combine these approaches. All algorithms have optimal worst-case time complexity and use linear space.
Plants sense changes in their orientation towards the vector of gravity and respond with directio... more Plants sense changes in their orientation towards the vector of gravity and respond with directional growth. Several metabolites in the signal transduction cascade have been identified. However, very little is known about the interaction between these sensing and signal transduction events and even less is known about their role in the differential growth response. Gravity induced changes in transcript abundance have been identified in Arabidopsis whole seedlings and root apices (Moseyko et al. 2002; Kimbrough et al. 2004). Gravity induced transcript abundance changes can be observed within less than 1 min after stimulation (Salinas-Mondragon et al. 2005). Gene expression however requires not only transcription but also translation of the mRNA. Translation can only occur when mRNA is associated with ribosomes, even though not all mRNA associated with ribosomes is actively translated. To approximate translational capacity we quantified whole genome transcript abundances in corn stem pulvini during the first hour after gravity stimulation in total and poly-ribosomal fractions. As in Arabidopsis root apices, transcript abundances of several clusters of genes responded to gravity stimulation. The vast majority of these transcripts were also found to associate with polyribosomes in the same temporal and quantitative pattern. These genes are transcriptionally regulated by gravity stimulation, but do not exhibit translational regulation. However, a small group of genes showed increased transcriptional regulation after gravity stimulation, but no association with polysomes. These transcripts likely are translationally repressed. The mechanism of translational repression for these transcripts is unknown. Based on the hypothesis that the genes essential for gravitropic responses should be expressed in most or all species, we compared the temporal gravity induced expression pattern of all orthologs identified between maize and Arabidopsis. A small group of genes showed high sequence identity as well as a conserved pattern of transcript abundance changes after gravity stimulation between corn pulvinus tissue and Arabidopsis root apices. The functions of these genes in gravitropic responses are currently being analyzed and should give us important information about evolutionary conserved elements in plant gravity signal transduction. (This research was funded by NASA). Kimbrough, J. M., R. Salinas-Mondragon, et al. (2004). "The Fast and Transient Transcriptional Network of Gravity and Mechanical Stimulation in the Arabidopsis Root Apex." Plant Physiol. 136(1): 2790-2805. Moseyko, N., T. Zhu, et al. (2002). "Transcription profiling of the early gravitropic response in Arabidopsis using high-density oligonucleotide probe microarrays." Plant Physiol 130(2): 720-8. Salinas-Mondragon, R., A. Brogan, et al. (2005). "Gravity and light: integrating transcriptional regulation in roots." Gravit Space Biol Bull 18(2): 121-2.
Background In eukaryotes, alternative splicing often generates multiple splice variants from a si... more Background In eukaryotes, alternative splicing often generates multiple splice variants from a single gene. Here weexplore the use of RNA sequencing (RNA-Seq) datasets to address the isoform quantification problem. Given a set of known splice variants, the goal is to estimate the relative abundance of the individual variants. Methods Our method employs a linear models framework to estimate the ratios of known isoforms in a sample. A key feature of our method is that it takes into account the non-uniformity of RNA-Seq read positions along the targeted transcripts. Results Preliminary tests indicate that the model performs well on both simulated and real data. In two publicly available RNA-Seq datasets, we identified several alternatively-spliced genes with switch-like, on/off expression properties, as well as a number of other genes that varied more subtly in isoform expression. In many cases, genes exhibiting differential expression of alternatively spliced transcripts were not differentially expressed at the gene level. Conclusions Given that changes in isoform expression level frequently involve a continuum of isoform ratios, rather than all-or-nothing expression, and that they are often independent of general gene expression changes, we anticipate that our research will contribute to revealing a so far uninvestigated layer of the transcriptome. We believe that, in the future, researchers will prioritize genes for functional analysis based not only on observed changes in gene expression levels, but also on changes in alternative splicing.
Recent research has demonstrated the utility of using supervised classification systems for autom... more Recent research has demonstrated the utility of using supervised classification systems for automatic identification of low quality microarray data. However, this approach requires annotation of a large training set by a qualified expert. In this paper we demonstrate the utility of an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and naive Bayes classification. On our test set, this system exhibits performance comparable to that of an analogous supervised learner constructed from the same training data.
Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of th... more Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We present an algorithm that finds in a family of k permutations of n elements all z common intervals in optimal O(kn+z) time and O(n) additional space. Additionally, we show how to adapt this algorithm to multichromosomal and circular permutations. This extends a result by Uno and Yagiura (Algorithmica 26:290–309, 2000) who present an algorithm to find all z common intervals of k=2 (regular) permutations in optimal O(n+z) time and O(n) space. To achieve our result, we introduce the set of irreducible intervals, a generating subset of the set of all common intervals of k permutations.
Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of th... more Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We present an algorithm that finds in a family of k permutations of n elements all K common intervals in optimal O(nk+K) time and O(n) additional space. This extends a result by Uno and Yagiura (Algorithmica 26, 290-309, 2000) who present an algorithm to find all K common intervals of k = 2 permutations in optimal O(n+K) time and O(n) space. To achieve our result, we introduce the set of irreducible intervals, a generating subset of the set of all common intervals of k permutations.
Comparing gene orders in completely sequenced genomes is a standard approach to locate clusters o... more Comparing gene orders in completely sequenced genomes is a standard approach to locate clusters of functionally associated genes. Often, gene orders are modeled as permutations. Given k permutations of n elements, a k-tuple of intervals of these permutations consisting of the same set of elements is called a common interval. We consider several problems related to common intervals in multiple genomes. We present an algorithm that finds all common intervals in a family of genomes, each of which might consist of several chromosomes. We present another algorithm that finds all common intervals in a family of circular permutations. A third algorithm finds all common intervals in signed permutations. We also investigate how to combine these approaches. All algorithms have optimal worst-case time complexity and use linear space.
Plants sense changes in their orientation towards the vector of gravity and respond with directio... more Plants sense changes in their orientation towards the vector of gravity and respond with directional growth. Several metabolites in the signal transduction cascade have been identified. However, very little is known about the interaction between these sensing and signal transduction events and even less is known about their role in the differential growth response. Gravity induced changes in transcript abundance have been identified in Arabidopsis whole seedlings and root apices (Moseyko et al. 2002; Kimbrough et al. 2004). Gravity induced transcript abundance changes can be observed within less than 1 min after stimulation (Salinas-Mondragon et al. 2005). Gene expression however requires not only transcription but also translation of the mRNA. Translation can only occur when mRNA is associated with ribosomes, even though not all mRNA associated with ribosomes is actively translated. To approximate translational capacity we quantified whole genome transcript abundances in corn stem pulvini during the first hour after gravity stimulation in total and poly-ribosomal fractions. As in Arabidopsis root apices, transcript abundances of several clusters of genes responded to gravity stimulation. The vast majority of these transcripts were also found to associate with polyribosomes in the same temporal and quantitative pattern. These genes are transcriptionally regulated by gravity stimulation, but do not exhibit translational regulation. However, a small group of genes showed increased transcriptional regulation after gravity stimulation, but no association with polysomes. These transcripts likely are translationally repressed. The mechanism of translational repression for these transcripts is unknown. Based on the hypothesis that the genes essential for gravitropic responses should be expressed in most or all species, we compared the temporal gravity induced expression pattern of all orthologs identified between maize and Arabidopsis. A small group of genes showed high sequence identity as well as a conserved pattern of transcript abundance changes after gravity stimulation between corn pulvinus tissue and Arabidopsis root apices. The functions of these genes in gravitropic responses are currently being analyzed and should give us important information about evolutionary conserved elements in plant gravity signal transduction. (This research was funded by NASA). Kimbrough, J. M., R. Salinas-Mondragon, et al. (2004). "The Fast and Transient Transcriptional Network of Gravity and Mechanical Stimulation in the Arabidopsis Root Apex." Plant Physiol. 136(1): 2790-2805. Moseyko, N., T. Zhu, et al. (2002). "Transcription profiling of the early gravitropic response in Arabidopsis using high-density oligonucleotide probe microarrays." Plant Physiol 130(2): 720-8. Salinas-Mondragon, R., A. Brogan, et al. (2005). "Gravity and light: integrating transcriptional regulation in roots." Gravit Space Biol Bull 18(2): 121-2.
Background In eukaryotes, alternative splicing often generates multiple splice variants from a si... more Background In eukaryotes, alternative splicing often generates multiple splice variants from a single gene. Here weexplore the use of RNA sequencing (RNA-Seq) datasets to address the isoform quantification problem. Given a set of known splice variants, the goal is to estimate the relative abundance of the individual variants. Methods Our method employs a linear models framework to estimate the ratios of known isoforms in a sample. A key feature of our method is that it takes into account the non-uniformity of RNA-Seq read positions along the targeted transcripts. Results Preliminary tests indicate that the model performs well on both simulated and real data. In two publicly available RNA-Seq datasets, we identified several alternatively-spliced genes with switch-like, on/off expression properties, as well as a number of other genes that varied more subtly in isoform expression. In many cases, genes exhibiting differential expression of alternatively spliced transcripts were not differentially expressed at the gene level. Conclusions Given that changes in isoform expression level frequently involve a continuum of isoform ratios, rather than all-or-nothing expression, and that they are often independent of general gene expression changes, we anticipate that our research will contribute to revealing a so far uninvestigated layer of the transcriptome. We believe that, in the future, researchers will prioritize genes for functional analysis based not only on observed changes in gene expression levels, but also on changes in alternative splicing.
Recent research has demonstrated the utility of using supervised classification systems for autom... more Recent research has demonstrated the utility of using supervised classification systems for automatic identification of low quality microarray data. However, this approach requires annotation of a large training set by a qualified expert. In this paper we demonstrate the utility of an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and naive Bayes classification. On our test set, this system exhibits performance comparable to that of an analogous supervised learner constructed from the same training data.
Uploads
Papers by Steffen Heber