Spot Weight Adaptation for Moving Target in Spot Scanning Proton Therapy.

Purpose: This study describes a real-time spot weight adaptation method in spot-scanning proton therapy for moving target or moving patient, so that the resultant dose distribution closely matches the planned dose distribution.

Materials And Methods: The method proposed in this study adapts the weight (MU) of the delivering pencil beam to that of the target spot; it will actually hit during patient/target motion. The target spot that a certain delivering pencil beam may hit relies on patient monitoring and/or motion modeling using four-dimensional (4D) CT.

Querying graphs in protein-protein interactions networks using feedback vertex set.

Recent techniques increase rapidly the amount of our knowledge on interactions between proteins. The interpretation of these new information depends on our ability to retrieve known substructures in the data, the Protein-Protein Interactions (PPIs) networks. In an algorithmic point of view, it is an hard task since it often leads to NP-hard problems.

Efficient tools for computing the number of breakpoints and the number of adjacencies between two genomes with duplicate genes.

Comparing genomes of different species is a fundamental problem in comparative genomics. Recent research has resulted in the introduction of different measures between pairs of genomes: for example, reversal distance, number of breakpoints, and number of common or conserved intervals. However, classical methods used for computing such measures are seriously compromised when genomes have several copies of the same gene scattered across them.

Exemplar longest common subsequence.

In this paper, we investigate the computational and approximation complexity of the Exemplar Longest Common Subsequence of a set of sequences (ELCS problem), a generalization of the Longest Common Subsequence problem, where the input sequences are over the union of two disjoint sets of symbols, a set of mandatory symbols and a set of optional symbols. We show that different versions of the problem are APX-hard even for instances with two sequences. Moreover, we show that the related problem of determining the existence of a feasible solution of the Exemplar Longest Common Subsequence of two sequences is NP-hard.

Comparing genomes with duplications: a computational complexity point of view.

In this paper, we are interested in the computational complexity of computing (dis)similarity measures between two genomes when they contain duplicated genes or genomic markers, a problem that happens frequently when comparing whole nuclear genomes. Recently, several methods ( [1], [2]) have been proposed that are based on two steps to compute a given (dis)similarity measure M between two genomes G_1 and G_2: first, one establishes a oneto- one correspondence between genes of G_1 and genes of G_2 ; second, once this correspondence is established, it defines explicitly a permutation and it is then possible to quantify their similarity using classical measures defined for permutations, like the number of breakpoints. Hence these methods rely on two elements: a way to establish a one-to-one correspondence between genes of a pair of genomes, and a (dis)similarity measure for permutations.

A pseudo-boolean framework for computing rearrangement distances between genomes with duplicates.

Computing genomic distances between whole genomes is a fundamental problem in comparative genomics. Recent researches have resulted in different genomic distance definitions, for example, number of breakpoints, number of common intervals, number of conserved intervals, and Maximum Adjacency Disruption number. Unfortunately, it turns out that, in presence of duplications, most problems are NP-hard, and hence several heuristics have been recently proposed.

Comparing gene expression networks in a multi-dimensional space to extract similarities and differences between organisms.

Motivation: Molecular evolution, which is classically assessed by comparison of individual proteins or genes between species, can now be studied by comparing co-expressed functional groups of genes. This approach, which better reflects the functional constraints on the evolution of organisms, can exploit the large amount of data generated by genome-wide expression analyses. However, it requires new methodologies to represent the data in a more accessible way for cross-species comparisons.

MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states.

Background: Information obtained by DNA microarray technology gives a rough snapshot of the transcriptome state, i.e., the expression level of all the genes expressed in a cell population at any given time.

yMGV: a cross-species expression data mining tool.

The yeast Microarray Global Viewer (yMGV @ http://transcriptome.ens.fr/ymgv) was created 3 years ago as a database that houses a collection of Saccharomyces cerevisiae and Schizosaccharo myces pombe microarray data sets published in 82 different articles.

Long mRNAs coding for yeast mitochondrial proteins of prokaryotic origin preferentially localize to the vicinity of mitochondria.

Background: Subcellular messenger RNA localization is important in most eukaryotic cells, even in unicellular organisms like yeast for which this process has been underestimated. Microarrays are rarely used to study subcellular mRNA localization at whole-genome level, but can be adapted to that purpose. This work focuses on studying the repartition of yeast nuclear transcripts encoding mitochondrial proteins between free cytosolic polysomes and polysomes bound to the mitochondrial outer membrane.

In Saccharomyces cerevisiae, ATP2 mRNA sorting to the vicinity of mitochondria is essential for respiratory function.

We recently demonstrated that polysome-associated mRNAs that co-isolate with mitochondria encode a subset of mitochondrial proteins, and that the 3' UTRs of these transcripts are essential for their localization to the vicinity of the organelle. To address the question of the involvement of the mRNA targeting process in mitochondrial biogenesis, we studied the role of ATP2 3' UTR. An altered ATP2 allele in which the 3' UTR was replaced by the ADH1 3' UTR exhibits properties supporting the importance of mRNA localization to the vicinity of mitochondria: (i) the mutated strain presents a respiratory dysfunction; (ii) mitochondrial import of the protein translated from the altered gene is strongly reduced, even though the precursor is addressed to the organelle surface; (iii) systematic deletions of ATP2 3' UTR revealed a 100 nucleotide element presenting RNA targeting properties.