Cell Edges Accumulate Gamma Tubulin Complex Components and Nucleate Microtubules following Cytokinesis in Arabidopsis thaliana

Microtubules emanate from distinct organizing centers in fungal and animal cells. In plant cells, by contrast, microtubules initiate from dispersed sites in the cell cortex, where they then self-organize into parallel arrays. Previous ultrastructural evidence suggested that cell edges participate in microtubule nucleation but so far there has been no direct evidence for this. Here we use live imaging to show that components of the gamma tubulin nucleation complex (GCP2 and GCP3) localize at distinct sites along the outer periclinal edge of newly formed crosswalls, and that microtubules grow predominantly away from these edges. These data confirm a role for cell edges in microtubule nucleation, and suggest that an asymmetric distribution of microtubule nucleation factors contributes to cortical microtubule organization in plants, in a manner more similar to other kingdoms than previously thought

The Development of Parallel Adaptive Sampling Algorithms for Analyzing Biological Networks

The availability of biological data in massive scales continues to represent unlimited opportunities as well as great challenges in bioinformatics research. Developing innovative data mining techniques and efficient parallel computational methods to implement them will be crucial in extracting useful knowledge from this raw unprocessed data, such as in discovering significant cellular subsystems from gene correlation networks. In this paper, we present a scalable combinatorial sampling technique, based on identifying maximum chordal subgraphs, that reduces noise from biological correlation networks, thereby making it possible to find biologically relevant clusters from the filtered network. We show how selecting the appropriate filter is crucial in maintaining the key structures from the original networks and uncovering new ones after removing noisy relationships. We also conduct one of the first comparisons in two important sensitivity criteria— the perturbation due to the vertex numbers of the network and perturbations due to data distribution. We demonstrate that our chordal-graph based filter is effective across many different vertex permutations, as is our parallel implementation of the sampling algorithm

Enrichment of raw sensor data to enable high-level queries

Sensor networks are increasingly used across various application domains. Their usage has the advantage of automated, often continuous, monitoring of activities and events. Ubiquitous sensor networks detect location of people and objects and their movement. In our research, we employ a ubiquitous sensor network to track the movement of players in a tennis match. By doing so, our goal is to create a detailed analysis of how the match progressed, recording points scored, games and sets, and in doing so, greatly reduce the eort of coaches and players who are required to study matches afterwards. The sensor network is highly efficient as it eliminates the need for manual recording of the match. However, it generates raw data that is unusable by domain experts as it contains no frame of reference or context and cannot be analyzed or queried. In this work, we present the UbiQuSE system of data transformers which bridges the gap between raw sensor data and the high-level requirements of domain specialists such as the tennis coach

Coronin 1C harbours a second actin-binding site that confers co-operative binding to F-actin

Dynamic rearrangement of actin filament networks is critical for cell motility, phagocytosis and endocytosis. Coronins facilitate these processes, in part, by their ability to bind F-actin (filamentous actin). We previously identified a conserved surface-exposed arginine (Arg30) in the β-propeller of Coronin 1B required for F-actin binding in vitro and in vivo. However, whether this finding translates to other coronins has not been well defined. Using quantitative actin-binding assays, we show that mutating the equivalent residue abolishes F-actin binding in Coronin 1A, but not Coronin 1C. By mutagenesis and biochemical competition, we have identified a second actin-binding site in the unique region of Coronin 1C. Interestingly, leading-edge localization of Coronin 1C in fibroblasts requires the conserved site in the β-propeller, but not the site in the unique region. Furthermore, in contrast with Coronin 1A and Coronin 1B, Coronin 1C displays highly co-operative binding to actin filaments. In the present study, we highlight a novel mode of coronin regulation, which has implications for how coronins orchestrate cytoskeletal dynamics

Parallel Adaptive Algorithms for Sampling Large Scale Networks

The study of real-world systems, represented as networks, has important application in many disciplines including social sciences [1], bioinformatics [2] and software engineering [3]. These networks are extremely large, and analyzing them is very expensive. Our research work involves developing parallel graph sampling methods for efficient analysis of gene correlation networks. Our sampling algorithms maintain important structural and informational properties of large unstructured networks. We focus on preserving the relative importance, based on combinatorial metrics, rather than the exact measures. We use a special subgraph technique, based on finding triangles called maximal chordal subgraphs, which maintains the highly connected portions of the network while increasing the distance between less connected regions. Our results show that even with significant reduction of the network we can obtain reliable subgraphs which conserve most of the relevant combinatorial and functional properties. Additionally, sampling reveals new functional properties which were previously undiscovered in the original system

Context-free pairs of groups I: Context-free pairs and graphs

Let $G$ be a finitely generated group, $A$ a finite set of generators and $K$ a subgroup of $G$. We call the pair $(G,K)$ context-free if the set of all words over $A$ that reduce in $G$ to an element of $K$ is a context-free language. When $K$ is trivial, $G$ itself is called context-free; context-free groups have been classified more than 20 years ago in celebrated work of Muller and Schupp as the virtually free groups. Here, we derive some basic properties of such group pairs. Context-freeness is independent of the choice of the generating set. It is preserved under finite index modifications of $G$ and finite index enlargements of $K$. If $G$ is virtually free and $K$ is finitely generated then $(G,K)$ is context-free. A basic tool is the following: $(G,K)$ is context-free if and only if the Schreier graph of $(G,K)$ with respect to $A$ is a context-free graph

GEMPAK: An arbitrary aircraft geometry generator

A computer program, GEMPAK, has been developed to aid in the generation of detailed configuration geometry. The program was written to allow the user as much flexibility as possible in his choices of configurations and the detail of description desired and at the same time keep input requirements and program turnaround and cost to a minimum. The program consists of routines that generate fuselage and planar-surface (winglike) geometry and a routine that will determine the true intersection of all components with the fuselage. This paper describes the methods by which the various geometries are generated and provides input description with sample input and output. Also included are descriptions of the primary program variables and functions performed by the various routines. The FORTRAN program GEMPAK has been used extensively in conjunction with interfaces to several aerodynamic and plotting computer programs and has proven to be an effective aid in the preliminary design phase of aircraft configurations