1,729 research outputs found
Strukturelle und funktionelle Charakterisierung zweier glycolytischer Enzyme des hyperthermophilen Archaeums Thermoproteus tenax
Hauptziel dieser Arbeit war es, die strukturellen und funktionellen Eigenschaften der Triosephosphat-Isomerase (TIM) und der Pyruvat-Kinase (PK) des hyperthermophilen Archaeums T. tenax zu charakterisieren und damit einen Beitrag zur AufklĂ€rung der Regulation des Embden-Meyerhof-Parnas-Weges (EMP-Weg) in diesem Organismus zu leisten. Auf der Basis der Struktur- und Funktionsdaten sollte auch eine Analyse thermoadaptiver Merkmale sowie phylogenetischer Studien durchgefĂŒhrt werden.
Im ersten Teil der Arbeit wurde das TIM-kodierende tpi-Gen aus T. tenax kloniert und sequenziert. Zu vergleichende Untersuchungen wurde die TIM von T. tenax ebenso wie die TIMs des mesophilen Methanogenen M. bryantii und des hyperthermophilen Methanogenen M. fervidus in E. coli experimentiert.
Das tpi-Gen von T. tenax ist mit dem Aconitase-Gen assoziiert und wird nach preliminĂ€ren Untersuchungen möglicherweise mit diesem kotranskribiert. Dabei liegt die Kopienzahl der Transkripte unter heterotrophen Wachstumsbedingungen deutlich höher als unter autotrophen und spricht fĂŒr die Regulation auf Transkriptebene.
Die TIM von T. tenax liegt nach den vorliegenden Untersuchungen ebenso wie die TIMs der hyperthermophilen Euryarchaeota M. fervidus und p. woesei als Tetramer vor. Im Gegensatz dazu sind alle bekannten TIMs aus Eucarya und Bacteria sowie die TIM von M. bryantii Dimere. Dies bestÀtigt einen Trend zur Bildung höherer Aggredationsformen, der inzwischen auch bei anderen Enzymen aus hyperthermophilen Organismen vorgefunden wurde und unter dem Aspekt der Thermoadaption interpretiert wird.
Der zweite Teil der Arbeit setzt sich mit der strukturellen und funktionellen Charakterisierung der PK auseinander. Das PK-kodierende pyk-Gen liegt isoliert im Genom von T.tenax und wird als monocistronische mRNS abgelesen. Die pyk-Transkriptmenge liegt in heterotrophen Zellen höher als in autotrophen Zellen und korreliert mit der PK-AktivitĂ€t in Zellen, die unter den entsprechenden trophischen Bedingungen angezogen wurden. Neben dieser Regulation auf Transkriptebene liegt eine Regulationsmöglichkeit auf Proteinebene vor: Das Enzym weist eine positive BindungskooperativitĂ€t fĂŒr das Substrat Phosphoenolpyruvat sowie Mg 2+- bzw. Mn 2+-Ionen auf. Die Ergebnisse deuten daraufhin, dass die PK neben der nicht-phosphorylierenden GAPDH einen wichtigen Kontrollpunkt im EMP-Weg von T. tenax darstellt, ĂŒber den der Organismus in die Lage versetzt wird, den Kohlenstofflux durch den Abbauweg kurzfristig (auf Proteinebene) und langfristig (durch genetische Regulation) zu Ă€ndern. Die phylogenetische Analyse zeigt, dass sich im Verlauf der Evolution zwei GroĂgruppen von PKs (PK I und PK II) gebildet haben. Die PKs der Eucarya, einige Enzyme von gram-positiven und gram-negativen Bacteria gehören zu der GroĂgruppe PK I, wĂ€hrend die andere Gruppe (PK II) einen GroĂteil der gram-negativen Bacteria, Myco- und Corynebacteria, plastidĂ€re Enzyme sowie die Archaea als monophyletische Gruppe umfaĂt. Die Topologie des Baums legt nahe, dass die eucaryalen PKs von einem proteobacterialen VorlĂ€uferenzym abstammen
Preprocessing of Affymetrix Exon Expression Arrays
The activity of genes can be captured by measuring the amount of messenger RNAs transcribed from the genes, or from their subunits called exons. In our study, we use the Affymetrix Human Exon ST v1.0 micro arrays to measure the activity of exon s in Neuroblastoma cancer patients. The purpose is to discover a small number of genes or exons that play important roles in differentiating high - risk patients fro m low - risk counterparts. Although the technology has been improved for the past 15 years, array measurements still can be contaminated by various factors, including human error. Since the number of arrays is often only few hundreds, atypical errors can hardly be canceled by large numbers of normal arrays. In this article we describe how we filter out low - quality arrays in a principled way, so that we can obtain more reliable results in downstream analyses
Computational Barriers to Estimation from Low-Degree Polynomials
One fundamental goal of high-dimensional statistics is to detect or recover
structure from noisy data. In many cases, the data can be faithfully modeled by
a planted structure (such as a low-rank matrix) perturbed by random noise. But
even for these simple models, the computational complexity of estimation is
sometimes poorly understood. A growing body of work studies low-degree
polynomials as a proxy for computational complexity: it has been demonstrated
in various settings that low-degree polynomials of the data can match the
statistical performance of the best known polynomial-time algorithms for
detection. While prior work has studied the power of low-degree polynomials for
the task of detecting the presence of hidden structures, it has failed to
address the estimation problem in settings where detection is qualitatively
easier than estimation.
In this work, we extend the method of low-degree polynomials to address
problems of estimation and recovery. For a large class of "signal plus noise"
problems, we give a user-friendly lower bound for the best possible mean
squared error achievable by any degree-D polynomial. To our knowledge, this is
the first instance in which the low-degree polynomial method can establish
low-degree hardness of recovery problems where the associated detection problem
is easy. As applications, we give a tight characterization of the low-degree
minimum mean squared error for the planted submatrix and planted dense subgraph
problems, resolving (in the low-degree framework) open problems about the
computational complexity of recovery in both cases.Comment: 38 page
Quantitatively consistent computation of coherent and incoherent radiation in particle-in-cell codes - a general form factor formalism for macro-particles
Quantitative predictions from synthetic radiation diagnostics often have to
consider all accelerated particles. For particle-in-cell (PIC) codes, this not
only means including all macro-particles but also taking into account the
discrete electron distribution associated with them. This paper presents a
general form factor formalism that allows to determine the radiation from this
discrete electron distribution in order to compute the coherent and incoherent
radiation self-consistently. Furthermore, we discuss a memory-efficient
implementation that allows PIC simulations with billions of macro-particles.
The impact on the radiation spectra is demonstrated on a large scale LWFA
simulation.Comment: Proceedings of the EAAC 2017, This manuscript version is made
available under the CC-BY-NC-ND 4.0 licens
Configurations with few crossings in topological graphs
AbstractIn this paper we study the problem of computing subgraphs of a certain configuration in a given topological graph G such that the number of crossings in the subgraph is minimum. The configurations that we consider are spanning trees, sât paths, cycles, matchings, and Îș-factors for Îșâ{1,2}. We show that it is NP-hard to approximate the minimum number of crossings for these configurations within a factor of k1âΔ for any Δ>0, where k is the number of crossings in G.We then give a simple fixed-parameter algorithm that tests in Oâ(2k) time whether G has a crossing-free configuration for any of the above, where the Oâ-notation neglects polynomial terms. For some configurations we have faster algorithms. The respective running times are Oâ(1.9999992k) for spanning trees and Oâ((3)k) for s-t paths and cycles. For spanning trees we also have an Oâ(1.968k)-time Monte-Carlo algorithm. Each Oâ(ÎČk)-time decision algorithm can be turned into an Oâ((ÎČ+1)k)-time optimization algorithm that computes a configuration with the minimum number of crossings
Finitary Coloring
Suppose that the vertices of are assigned random colors via a
finitary factor of independent identically distributed (iid) vertex-labels.
That is, the color of vertex is determined by a rule that examines the
labels within a finite (but random and perhaps unbounded) distance of ,
and the same rule applies at all vertices. We investigate the tail behavior of
if the coloring is required to be proper (that is, if adjacent vertices
must receive different colors). When , the optimal tail is given by a
power law for 3 colors, and a tower (iterated exponential) function for 4 or
more colors (and also for 3 or more colors when ). If proper coloring is
replaced with any shift of finite type in dimension 1, then, apart from trivial
cases, tower function behavior also applies.Comment: 35 pages, 3 figure
- âŠ