6308143
Geometry of gene expression dynamics
MOTIVATION
A gene expression trajectory moves through a high dimensional space where each axis represents the mRNA abundance of a different gene. Genome wide gene expression has a dynamic structure, especially in studies of development and temporal response. Both visualization and analyses of such data require an explicit attention to the temporal structure.


RESULTS
Using three cell cycle trajectories from Saccharomyces cerevisiae to illustrate, we present several techniques which reveal the geometry of the data. We import phase-delay time plots from chaotic systems theory as a dynamic data visualization device and show how these plots capture important aspects of the trajectories. We construct an objective function to find an optimal two-dimensional projection of the cell cycle, demonstrate that the system returns to this plane after three different initial perturbations, and explore the conditions under which this geometric approach outperforms standard approaches such as singular value decomposition and Fourier analysis. Finally, we show how a geometric analysis can isolate distinct parts of the trajectories, in this case the initial perturbation versus the cell cycle.


CONTACT
junhyong.kim@yale.edu
1278377
A Tree Obscured By Vines: Horizontal Gene Transfer and the Median Tree Method of Estimating Species Phylogeny
A phylogeny is a tree graph representation of genealogical relationships between biological objects. It is of general interest to estimate the phylogeny of whole organisms (species trees) using bio-molecular sequences. When multiple sequences are available for each organism such as with whole genome data, individual phylogenies estimated by each molecule (gene trees) may not be concordant. The lack of concordance may be due to actual biological mechanisms such as horizontal transfer of the molecules. Here, we present a new phylogeny estimation method designed to estimate the species tree despite such horizontal transfer. It uses the idea that horizontal transfer distorts distance relationships between pairs of species but a median estimate of the distances is robust to such distortions. We demonstrate the utility of our method using a simulation study.
199137
Scaling of Accuracy in Extremely Large Phylogenetic Trees
The accuracy of phylogenetic inference was examined in simulated data sets up to nearly 10,000 taxa, the size of the largest set of homologous genes in existing molecular sequence databases. Even with a simple search algorithm (maximum parsimony without branch swapping), the number of characters needed to estimate 80% of a tree correctly can scale remarkably well at optimal substitution rates (on the order of log N, where N is the number of taxa). In other words, the number of taxa in an analysis can be doubled and only an arithmetic increase in the number of characters is required to maintain the same level of accuracy. Even substitution rates that are much higher than normally used in phylogenetic studies did not affect the scaling too adversely. However, scaling is usually worse than log N for more stringent levels of accuracy. Moreover, errors are not distributed randomly throughout the tree. Shallow nodes are remarkably easy to reconstruct and display favourable log-linear scaling. The deepest nodes are extremely difficult to reconstruct accurately, even with branch swapping, and the scaling is poor. Therefore, the strategy of sequencing large numbers of homologous genes may not always provide global solutions to extreme phylogenetic problems and alternative strategies may be required.
2551048
Computers Are from Mars, Organisms Are from Venus
Biology and computer science share a natural affinity. Physicist Erwin Schrodinger envisioned life as an aperiodic crystal, observing that the organizing structure of life is neither completely regular, like a pure crystal, nor completely chaotic and without structure, like dust in the wind. Perhaps this is why biological information has never satisfactorily yielded to classical mathematical analysis. Machine computations combine elegant algorithms with brute-force calculations, which seems a reasonable approach to this aperiodic structure. Likewise, computing seeks to create a machine that can flexibly solve diverse problems. In nature, such plastic problem solving resides uniquely in the domain of organic matter. Thus, examining how organisms solve problems can lead to new computation and algorithm development approaches that devour the problems that are so easy to approach using a computer, yet so difficult to tackle in the laboratory. The paper discusses the two most successful uses of computers in biology, comparative sequence analysis and in silico cloning. It considers DNA computing and genetic algorithms.
32992816
A Combinatorial Toolbox for Protein Sequence Design and Landscape Analysis in the Grand Canonical Model
In modern biology, one of the most important research problems is to understand how protein sequences fold into their native 3D structures. To investigate this problem at a high level, one wishes to analyze the protein landscapes, i.e., the structures of the space of all protein sequences and their native 3D structures. Perhaps the most basic computational problem at this level is to take a target 3D structure as input and design a fittest protein sequence with respect to one or more fitness functions of the target 3D structure. We develop a toolbox of combinatorial techniques for protein landscape analysis in the Grand Canonical model of Sun, Brem, Chan, and Dill. The toolbox is based on linear programming, network flow, and a linear-size representation of all minimum cuts of a network. It not only substantially expands the network flow technique for protein sequence design in Kleinberg's seminal work but also is applicable to a considerably broader collection of computational problems than those considered by Kleinberg. We have used this toolbox to obtain a number of efficient algorithms and hardness results. We have further used the algorithms to analyze 3D structures drawn from the Protein Data Bank and have discovered some novel relationships between such native 3D structures and the Grand Canonical model.
40331728
Efficient 2-D Convolution Algorithm with the Single-Data Multiple Kernel Approach
Abstract A fast implementation of convolution operation is described. The implementation takes advantage of various properties of commonly used kernels. First, the kernel elements are analyzed and rearranged, grouping the kernel elements of the same absolute value together and arranging trivial multiplication cases separately. Then the sequence of computing convolution sums is modified so that all the kernel elements could be multiplied by the same data element at each step. This new algorithm significantly reduces the number of multiplication operations for most widely used kernels. Our experiment shows that the performance improvement of two to seven over the direct implementation is achievable for most kernels. The required overhead (extra memory and preprocessing) is proportional to the kernel size and is negligible.
2978705
Reconstructing the Temporal Ordering of Biological Samples Using Microarray Data
MOTIVATION
Accurate time series for biological processes are difficult to estimate due to problems of synchronization, temporal sampling and rate heterogeneity. Methods are needed that can utilize multi-dimensional data, such as those resulting from DNA microarray experiments, in order to reconstruct time series from unordered or poorly ordered sets of observations.


RESULTS
We present a set of algorithms for estimating temporal orderings from unordered sets of sample elements. The techniques we describe are based on modifications of a minimum-spanning tree calculated from a weighted, undirected graph. We demonstrate the efficacy of our approach by applying these techniques to an artificial data set as well as several gene expression data sets derived from DNA microarray experiments. In addition to estimating orderings, the techniques we describe also provide useful heuristics for assessing relevant properties of sample datasets such as noise and sampling intensity, and we show how a data structure called a PQ-tree can be used to represent uncertainty in a reconstructed ordering.


AVAILABILITY
Academic implementations of the ordering algorithms are available as source code (in the programming language Python) on our web site, along with documentation on their use. The artificial 'jelly roll' data set upon which the algorithm was tested is also available from this web site. The publicly available gene expression data may be found at http://genome-www.stanford.edu/cellcycle/ and http://caulobacter.stanford.edu/CellCycle/.
214797856
Temporal Streaming of Shared Memory
Coherent read misses in shared-memory multiprocessors account for a substantial fraction of execution time in many important scientific and commercial workloads. We propose Temporal Streaming, to eliminate coherent read misses by streaming data to a processor in advance of the corresponding memory accesses. Temporal streaming dynamically identifies address sequences to be streamed by exploiting two common phenomena in shared-memory access patterns: (1) temporal address correlation � groups of shared addresses tend to be accessed together and in the same order, and (2) temporal stream locality � recently-accessed address streams are likely to recur. We present a practical design for temporal streaming. We evaluate our design using a combination of trace-driven and cycle-accurate full-system simulation of a cache-coherent distributed shared-memory system. We show that temporal streaming can eliminate 98% of coherent read misses in scientific applications, and between 43% and 60% in database and web server workloads. Our design yields speedups of 1.07 to 3.29 in scientific applications, and 1.06 to 1.21 in commercial workloads.
42381820
An Improvement of VeriSign's Key Roaming Service Protocol
In the past two or three years, most major Public Key Infrastructure (PKI) vendors have released products which allow users to roam from one machine to another without having to manually manage the export and import of their credentials such as private keys and corresponding certificates onto temporary media like diskettes. In this paper, we survey three popular key roaming products of Baltimore's, Entrust's and VeriSign's. We also propose key roaming system which improves VeriSign's roaming service and analyze its security.
4595504
Visualization and evaluation of clusters for exploratory analysis of gene expression data
Clustering algorithms have been shown to be useful to explore large-scale gene expression profiles. Visualization and objective evaluation of clusters are two important considerations when users are selecting different clustering algorithms, but they are often overlooked. The developments of a framework and software tools that implement comprehensive data visualization and objective measures of cluster quality are crucial. In this paper, we describe a theoretical framework and formalizations for consistently developing clustering algorithms. A new clustering algorithm was developed within the proposed framework. We demonstrate that a theoretically sound principle can be uniformly applied to the developments of cluster-optimization function, comprehensive data-visualization strategy, and objective cluster-evaluation measures as well as actual implementation of the principle. Cluster consistency and quality measures of the algorithm are rigorously evaluated against those of popular clustering algorithms for gene expression data analysis (K-means and self-organizing maps), in four data sets, yielding promising results.