Geographically weighted visualization: interactive graphics for scale-varying exploratory analysis

We introduce a series of geographically weighted (GW) interactive graphics, or geowigs, and use them to explore spatial relationships at a range of scales. We visually encode information about geographic and statistical proximity and variation in novel ways through gw-choropleth maps, multivariate gw-boxplots, gw-shading and scalograms. The new graphic types reveal information about GW statistics at several scales concurrently. We impement these views in prototype software containing dynamic links and GW interactions that encourage exploration and refine them to consider directional geographies. An informal evaluation uses interactive GW techniques to consider Guerry's dataset of 'moral statistics', casting doubt on correlations originally proposed through visual analysis, revealing new local anomalies and suggesting multivariate geographic relationships. Few attempts at visually synthesising geography with multivariate statistical values at multiple scales have been reported. The geowigs proposed here provide informative representations of multivariate local variation, particularly when combined with interactions that coordinate views and result in gw-shading. We argue that they are widely applicable to area and point-based geographic data and provide a set of methods to support visual analysis using GW statistics through which the effects of geography can be explored at multiple scales.     

Pathline: A Tool For Comparative Functional Genomics

Biologists pioneering the new field of comparative functional genomics attempt to infer the mechanisms of gene regulation by looking for similarities and differences of gene activity over time across multiple species. They use three kinds of data: functional data such as gene activity measurements, pathway data that represent a series of reactions within a cellular process, and phylogenetic relationship data that describe the relatedness of species. No existing visualization tool can visually encode the biologically interesting relationships between multiple pathways, multiple genes, and multiple species. We tackle the challenge of visualizing all aspects of this comparative functional genomics dataset with a new interactive tool called Pathline. In addition to the overall characterization of the problem and design of Pathline, our contributions include two new visual encoding techniques. One is a new method for linearizing metabolic pathways that provides appropriate topological information and supports the comparison of quantitative data along the pathway. The second is the curvemap view, a depiction of time series data for comparison of gene activity and metabolite levels across multiple species. Pathline was developed in close collaboration with a team of genomic scientists. We validate our approach with case studies of the biologists’ use of Pathline and report on how they use the tool to confirm existing findings and to discover new scientific insights.     

Lark: Coordinating Co-located Collaboration with Information Visualization

Large multi-touch displays are expanding the possibilities of multiple-coordinated views by allowing multiple people to interact with data in concert or independently. We present Lark, a system that facilitates the coordination of interactions with information visualizations on shared digital workspaces. We focus on supporting this coordination according to four main criteria: scoped interaction, temporal flexibility, spatial flexibility, and changing collaboration styles. These are achieved by integrating a representation of the information visualization pipeline into the shared workspace, thus explicitly indicating coordination points on data, representation, presentation, and view levels. This integrated meta-visualization supports both the awareness of how views are linked and the freedom to work in concert or independently. Lark incorporates these four main criteria into a coherent visualization collaboration interaction environment by providing direct visual and algorithmic support for the coordination of data analysis actions over shared large displays.     

BIOSITE: a program for the interactive comparison of aligned homologous protein sequences.

A program, BIOSITE, providing for the interactive visual comparison of aligned homologous amino-acid sequences is presented, including an example of its application. The program allows for two types of comparison sequence to be generated: an 'identity' sequence and a 'difference' sequence. These may be used on subsets of sequences and in further comparisons to identify candidate sites involved in a distinct functional property. The program should prove a useful tool for biologists engaged in understanding sequence--function relationships.     

Sequence Surveyor: leveraging overview for scalable genomic alignment visualization

In this paper, we introduce overview visualization tools for large-scale multiple genome alignment data. Genome alignment visualization and, more generally, sequence alignment visualization are an important tool for understanding genomic sequence data. As sequencing techniques improve and more data become available, greater demand is being placed on visualization tools to scale to the size of these new datasets. When viewing such large data, we necessarily cannot convey details, rather we specifically design overview tools to help elucidate large-scale patterns. Perceptual science, signal processing theory, and generality provide a framework for the design of such visualizations that can scale well beyond current approaches. We present Sequence Surveyor, a prototype that embodies these ideas for scalable multiple whole-genome alignment overview visualization. Sequence Surveyor visualizes sequences in parallel, displaying data using variable color, position, and aggregation encodings. We demonstrate how perceptual science can inform the design of visualization techniques that remain visually manageable at scale and how signal processing concepts can inform aggregation schemes that highlight global trends, outliers, and overall data distributions as the problem scales. These techniques allow us to visualize alignments with over 100 whole bacterial-sized genomes.     

IBM microcomputer programs that analyze DNA sequences for tRNA genes

A set of four computer programs that search DNA sequence data files for transfer RNA genes have been written in IBM (Microsoft) BASIC for the IBM personal computer. These programs locate and plot predicted secondary structures of tRNA genes in the cloverleaf conformation. The set of programs are applicable to eukaryotic tRNA genes, including those containing intervening sequences, and to prokaryotic and mitochondrial tRNA genes. In addition, two of the programs search up to 150 residues downstream of tRNA gene sequences for possible eukaryotic RNA polymerase III termination sites comprised of at least four consecutive T residues. Molecular biologists studying a variety of gene sequence and flanking regions can use these programs to search for the additional presence of tRNA genes. Furthermore, investigators studying tRNA gene structure-to-function relationships would not need to do extensive restriction mapping to locate tRNA gene sequences within their cloned DNA fragments.     

Gremlin: an interactive visualization model for analyzing genomic rearrangements

In this work we present, apply, and evaluate a novel, interactive visualization model for comparative analysis of structural variants and rearrangements in human and cancer genomes, with emphasis on data integration and uncertainty visualization. To support both global trend analysis and local feature detection, this model enables explorations continuously scaled from the high-level, complete genome perspective, down to the low-level, structural rearrangement view, while preserving global context at all times. We have implemented these techniques in Gremlin, a genomic rearrangement explorer with multi-scale, linked interactions, which we apply to four human cancer genome data sets for evaluation. Using an insight-based evaluation methodology, we compare Gremlin to Circos, the state-of-the-art in genomic rearrangement visualization, through a small user study with computational biologists working in rearrangement analysis. Results from user study evaluations demonstrate that this visualization model enables more total insights, more insights per minute, and more complex insights than the current state-of-the-art for visual analysis and exploration of genome rearrangements.     

Parallel Genomic Alignments on the Cell Broadband Engine

Genomic alignments, as a means to uncover evolutionary relationships among organisms, are a fundamental tool in computational biology. There is considerable recent interest in using the Cell Broadband Engine, a heterogeneous multicore chip that provides high performance, for biological applications. However, work in genomic alignments so far has been limited to computing optimal alignment scores using quadratic space for the basic global/local alignment problem. In this paper, we present a comprehensive study of developing alignment algorithms on the Cell, exploiting its thread and data level parallelism features. First, we develop a parallel implementation on the Cell that computes optimal alignments and adopts Hirschberg's linear space technique. The former is essential, as merely computing optimal alignment scores is not useful, while the latter is needed to permit alignments of longer sequences. We then present Cell implementations of two advanced alignment techniques-spliced alignments and syntenic alignments. Spliced alignments are useful in aligning mRNA sequences with corresponding genomic sequences to uncover the gene structure. Syntenic alignments are used to discover conserved exons and other sequences between long genomic sequences from different organisms. We present experimental results for these three types of alignments on 16 Synergistic Processing Elements of the IBM QS20 dual-Cell blade system.     

Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks

Many biologists, ecologists, and conservationists are interested in the possibilities that remote sensing offers for their daily work and study site analyses as well as for the assessment of biodiversity. However, due to differing technical backgrounds and languages, cross-sectorial communication between this group and remote-sensing scientists is often hampered. Hardly any really comprehensive studies exist that are directed towards the conservation community and provide a solid overview of available Earth observation sensors and their different characteristics. This article presents, categorizes, and discusses what spaceborne remote sensing has contributed to the study of animal and vegetation biodiversity, which different types of variables of value for the biodiversity community can be derived from remote-sensing data, and which types of spaceborne sensor data are available for which time spans, and at which spatial and temporal resolution. We categorize all current and important past sensors with respect to application fields relevant for biologists, ecologists, and conservationists. Furthermore, sensor gaps and current challenges for Earth observation with respect to data access and provision are presented.     

Querying neXtProt nanopublications and their value for insights on sequence variants and tissue expression

Understanding how genetic differences between individuals impact the regulation, expression, and ultimately function of proteins is an important step toward realizing the promise of personal medicine. There are several technical barriers hindering the transition of biological knowledge into the applications relevant to precision medicine. One important challenge for data integration is that new biological sequences (proteins, DNA) have multiple issues related to interoperability potentially creating a quagmire in the published data, especially when different data sources do not appear to be in agreement. Thus, there is an urgent need for systems and methodologies to facilitate the integration of information in a uniform manner to allow seamless querying of multiple data types which can illuminate, for example, the relationships between protein modifications and causative genomic variants. Our work demonstrates for the first time how semantic technologies can be used to address these challenges using the nanopublication model applied to the neXtProt data set, a curated knowledgebase of information about human proteins. We have applied the nanopublication model to demonstrate querying over several named graphs, including the provenance information associated with the curated scientific assertions from neXtProt. We show by way of use cases using sequence variations, post-translational modifications (PTMs) and tissue expression, that querying the neXtProt nanopublication implementation is a credible approach for expanding biological insight.     

An Immune-Evolutionary Algorithm for Multiple Rearrangements of Gene Expression Data

Microarray technologies are employed to simultaneously measure expression levels of thousands of genes. Data obtained from such experiments allow inference of individual gene functions, help to identify genes from specific tissues, to analyze the behavior of gene expression levels under various environmental conditions and under different cell cycle stages, and to identify inappropriately transcribed genes and several genetic diseases, among many other applications. As thousands of genes may be involved in a microarray experiment, computational tools for organizing and providing possible visualizations of the genes and their relationships are crucial to the understanding and analysis of the data. This work proposes an algorithm based on artificial immune systems for organizing gene expression data in order to simultaneously reveal multiple features in large amounts of data. A distinctive property of the proposed algorithm is the ability to provide a diversified set of high-quality rearrangements of the genes, opening up the possibility of identifying various co-regulated genes from representative graphical configurations of the expression levels. This is a very useful approach for biologists, because several co-regulated genes may exist under different conditions.     

GeneShelf: A Web-based Visual Interface for Large Gene Expression Time-Series Data Repositories

A widespread use of high-throughput gene expression analysis techniques enabled the biomedical research community to share a huge body of gene expression datasets in many public databases on the web. However, current gene expression data repositories provide static representations of the data and support limited interactions. This hinders biologists from effectively exploring shared gene expression datasets. Responding to the growing need for better interfaces to improve the utility of the public datasets, we have designed and developed a new web-based visual interface entitled GeneShelf (http://bioinformatics.cnmcresearch.org/GeneShelf). It builds upon a zoomable grid display to represent two categorical dimensions. It also incorporates an augmented timeline with expandable time points that better shows multiple data values for the focused time point by embedding bar charts. We applied GeneShelf to one of the largest microarray datasets generated to study the progression and recovery process of injuries at the spinal cord of mice and rats. We present a case study and a preliminary qualitative user study with biologists to show the utility and usability of GeneShelf.     

Cross-Filtered Views for Multidimensional Visual Analysis

Analysis of multidimensional data often requires careful examination of relationships across dimensions. Coordinated multiple view approaches have become commonplace in visual analysis tools because they directly support expression of complex multidimensional queries using simple interactions. However, generating such tools remains difficult because of the need to map domain-specific data structures and semantics into the idiosyncratic combinations of interdependent data and visual abstractions needed to reveal particular patterns and distributions in cross-dimensional relationships. This paper describes: 1) a method for interactively expressing sequences of multidimensional set queries by cross-filtering data values across pairs of views and 2) design strategies for constructing coordinated multiple view interfaces for cross-filtered visual analysis of multidimensional data sets. Using examples of cross-filtered visualizations of data from several different domains, we describe how cross-filtering can be modularized and reused across designs, flexibly customized with respect to data types across multiple dimensions, and incorporated into more wide-ranging multiple view designs. We also identify several important limitations of the approach. The demonstrated analytic utility of these examples suggests that cross-filtering is a suitable design pattern for instantiation in a wide variety of visual analysis tools.     

The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis

Traditional remote sensing techniques allow the assessment of green plant biomass, and therefore plant photosynthetic capacity. However, detecting how much of this capacity is actually realized is a more challenging goal. Is it possible to remotely assess actual carbon fluxes? Can this be done at leaf, canopy and ecosystem scales and at different temporal scales? Different approaches can be used to answer these questions. Among them, the Photochemical Reflectance Index (PRI) derived from narrow-band spectroradiometers is a spectral index increasingly being used as an indicator of photosynthetic efficiency. We examined and synthesized the scientific literature on the relationships between PRI and several ecophysiological variables across a range of plant functional types and ecosystems at the leaf, canopy and ecosystem levels and at the daily and seasonal time scales. Our analysis shows that although the strength of these relationships varied across vegetation types, levels of organization and temporal scales, in most reviewed articles PRI was a good predictor of photosynthetic efficiency or related variables with performances at least as good as the widely used NDVI as indicator of green biomass. There are possible confounding factors related to the intensity of the physiological processes linked to the PRI signals, to the structure of the canopies and to the illumination and viewing angles that warrant further studies, and it is expected that the utility of PRI will vary with the ecosystem in question due to contrasting environmental constraints, evolutionary strategies, and radiation use efficiency (RUE; the ratio between carbon uptake and light absorbed by vegetation) variability. Clearly, more research comparing ecosystem responses is warranted. Additionally, like any 2-band index that is affected by multiple factors, the interpretation of PRI can be readily confounded by multiple environmental variables, and further work is needed to understand and constrain these effects. Despite these limitations, this review shows an emerging consistency of the RUE-PRI relationship that suggests a surprising degree of functional convergence of biochemical, physiological and structural components affecting leaf, canopy and ecosystem carbon uptake efficiencies. PRI accounted for 42%, 59% and 62% of the variability of RUE at the leaf, canopy and ecosystem respective levels in unique exponential relationships for all the vegetation types studied. It seems thus that by complementing the estimations of the fraction of photosynthetically active radiation intercepted by the vegetation (FPAR), estimated with NDVI-like indices, PRI enables improved assessment of carbon fluxes in leaves, canopies and many of the ecosystems of the world from ground, airborne and satellite sensors.     

Software Trapping: A Strategy for Finding Genes in Large Genomic Regions

We present an approach to the gene identification phase of positional cloning that combines sparse sampling of DNA sequences from large genomic regions with computational analysis. We call the method "software trapping." The goal is to find coding exons while avoiding massive DNA sequence determination and contig assembly. Instead, rapid sequence sampling is combined with exon screening software such as a newly developed package called XPOUND to identify coding sequences. We have tested the approach using a set of model genomic sequences with known intron/exon structures as well as with bona fide P1 genomic clones. The results suggest that the strategy is a useful complement to other methods for finding genes in poorly characterized regions of genomes.     

超级多重基因组序列比对算法

大量同源的长基因组序列的多重比对需要高效率的比对算法。论文开发出一个新的比对工具“超级多重基因组比对”(简称SMGA),该系统是建立在序列突变与比对的“模代数”理论基础上专为长基因组序列的多重比对设计的。SMGA在一台主频2.8G的PC机上完成平均长度约5M的9条有机菌基因组的多重比对的时间大约为35min。论文还使用模拟数据对SMGA的比对精确度做了估计。     

Automatic detection of conserved base pairing patterns in RNA virus genomes.

Almost all RNA molecules--and consequently also almost all subsequences of a large RNA molecule-form secondary structures. The presence of secondary structure in itself therefore does not indicate any functional significance. In fact, we cannot expect a conserved secondary structure for all parts of a viral genome or a mRNA, even if there is a significant level of sequence conservation. We present a novel method for detecting conserved RNA secondary structures in a family of related RNA sequences. The method is based on combining the prediction of base pair probability matrices and comparative sequence analysis. It can be applied to small sets of long sequences and does not require a prior knowledge of conserved sequence or structure motifs. As such it can be used to scan large amounts of sequence data for regions that warrant further experimental investigation. Applications to complete genomic RNAs of some viruses show that in all cases the known secondary structure features are identified. In addition, we predict a substantial number of conserved structural elements which have not been described so far.     

Relationships between memory models

There have been many proposals of shared memory systems, each one providing different types of memory coherence for interprocess communication. However, they have usually been defined using different formalisms. This makes it difficult to compare among them the different proposals put forward. In this paper we present a formal framework for specifying memory models with different coherency properties. We specify most of the known shared memory models using our framework, showing some of the relationships that hold among them.     

基于Movielens电影数据的可视分析

目前,随着电影数据逐渐被人们获取,关于电影数据的研究可以给人们带来很多启发。分析电影流派的演变规律,可以为导演提供电影题材建议;分析经济和电影之间的关系,可以找到电影演变的原因;研究高评分电影在时间上的规律,可以指导导演选择电影的上映时间。但是,由于电影包含电影名称、所属流派、评分等多重属性,一般的研究方法不足以发现并直观地呈现电影数据隐含的规律。用可视化与可视分析的方法分析电影数据,设计了一系列相互关联的可视化视图,从多个时间尺度角度分析电影流派的时间演变,通过增长率曲线图研究电影数量和经济的相关关系,并设计饼图集来发现高评分电影在时间、流派上的规律。