Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664345
P. D. H. Ciechomski, Michael Klann, R. Mange, H. Koeppl
Systems-oriented research accelerates our understanding of biological processes and helps in identifying novel drug candidates. However, development of good models and our intuition is hampered by the biological complexity. To be able to see how candidate models evolve in front of the user in an interactive virtual 3D cell at various zoom levels, therefore is a crucial aspect and a challenging problem. The motivation for creating the ZigCell3D software, is thus a holistic view ranging from being able to change model parameters, see how they affect 3D versions of the cell at molecular levels, while at the same time being able to verify the simulated model against a real experimental fluorescence microscopy image. ZigCell3D is a virtual 3D whiteboard approach to chemical reaction modelling. It aims to provide a realtime interactive environment, where complex biophysics research is turned into a creative and game-like 3D environment. The complete system entails modelling, simulation and visualisation as part of a unified framework. The core visualisation is based on a multi-core parallel C/C++ ray tracing engine, that builds a complete 3D iso-surface model of the cell, its organelles and molecules down to the atomic level using PDB files. The simulator itself is based on coarse-grained Brownian motion of the individual molecules, which is visualised in detail in a tightly coupled manner. Using a virtual fluorescence microscope the virtual simulation environment can be benchmarked against real life experimental data.
{"title":"From biochemical reaction networks to 3D dynamics in the cell: The ZigCell3D modeling, simulation and visualisation framework","authors":"P. D. H. Ciechomski, Michael Klann, R. Mange, H. Koeppl","doi":"10.1109/BioVis.2013.6664345","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664345","url":null,"abstract":"Systems-oriented research accelerates our understanding of biological processes and helps in identifying novel drug candidates. However, development of good models and our intuition is hampered by the biological complexity. To be able to see how candidate models evolve in front of the user in an interactive virtual 3D cell at various zoom levels, therefore is a crucial aspect and a challenging problem. The motivation for creating the ZigCell3D software, is thus a holistic view ranging from being able to change model parameters, see how they affect 3D versions of the cell at molecular levels, while at the same time being able to verify the simulated model against a real experimental fluorescence microscopy image. ZigCell3D is a virtual 3D whiteboard approach to chemical reaction modelling. It aims to provide a realtime interactive environment, where complex biophysics research is turned into a creative and game-like 3D environment. The complete system entails modelling, simulation and visualisation as part of a unified framework. The core visualisation is based on a multi-core parallel C/C++ ray tracing engine, that builds a complete 3D iso-surface model of the cell, its organelles and molecules down to the atomic level using PDB files. The simulator itself is based on coarse-grained Brownian motion of the individual molecules, which is visualised in detail in a tightly coupled manner. Using a virtual fluorescence microscope the virtual simulation environment can be benchmarked against real life experimental data.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122473715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664341
Tan Khoa Nguyen, T. Ropinski
Multiple sequence alignment (MSA) is essential as an initial step in studying molecular phylogeny as well as during the identification of genomic rearrangements. Recent advances in sequencing techniques have led to a tremendous increase in the number of sequences to be analyzed. As a result, a greater demand is being placed on visualization techniques, as they have the potential to reveal the underlying information in large-scale MSAs. In this work, we present a novel visualization technique for conveying the patterns in large-scale MSAs. By applying gradient vector flow analysis to the MSA data, we can extract and visually emphasize conservations and other patterns that are relevant during the MSA exploration process. In contrast to the traditional visual representation of MSAs, which exploits color-coded tables, the proposed visual metaphor allows us to provide an overview of large MSAs as well as to highlight global patterns, outliers, and data distributions. We will motivate and describe the proposed algorithm, and further demonstrate its application to large-scale MSAs.
{"title":"Large-scale multiple sequence alignment visualization through gradient vector flow analysis","authors":"Tan Khoa Nguyen, T. Ropinski","doi":"10.1109/BioVis.2013.6664341","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664341","url":null,"abstract":"Multiple sequence alignment (MSA) is essential as an initial step in studying molecular phylogeny as well as during the identification of genomic rearrangements. Recent advances in sequencing techniques have led to a tremendous increase in the number of sequences to be analyzed. As a result, a greater demand is being placed on visualization techniques, as they have the potential to reveal the underlying information in large-scale MSAs. In this work, we present a novel visualization technique for conveying the patterns in large-scale MSAs. By applying gradient vector flow analysis to the MSA data, we can extract and visually emphasize conservations and other patterns that are relevant during the MSA exploration process. In contrast to the traditional visual representation of MSAs, which exploits color-coded tables, the proposed visual metaphor allows us to provide an overview of large MSAs as well as to highlight global patterns, outliers, and data distributions. We will motivate and describe the proposed algorithm, and further demonstrate its application to large-scale MSAs.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130452854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BIOVIS.2013.6664351
R. Ruddle, W. Fateen, D. Treanor, P. Sondergeld, P. Quirke
The scale of comparative genomics data frequently overwhelms current data visualization methods on conventional (desktop) displays. This paper describes two types of solution that take advantage of wall-sized high-resolution displays (WHirDs), which have orders of magnitude more display real estate (i.e., pixels) than desktop displays. The first allows users to view detailed graphics of copy number variation (CNV) that were output by existing software. A WHirD's resolution allowed a 10x increase in the granularity of bioinformatics output that was feasible for users to visually analyze, and this revealed a pattern that had previously been smoothed out from the underlying data. The second involved interactive visualization software that was innovative because it uses a music score metaphor to lay out CNV data, overcomes a perceptual distortion caused by amplification/deletion thresholds, uses filtering to reduce graphical data overload, and is the first comparative genomics visualization software that is designed to leverage a WHirD's real estate. In a field evaluation, a clinical user discovered a fundamental error in the way their data had been processed, and established confidence in the software by using it to `find' known genetic patterns in hepatitis C-driven hepatocellular cancer.
{"title":"Leveraging wall-sized high-resolution displays for comparative genomics analyses of copy number variation","authors":"R. Ruddle, W. Fateen, D. Treanor, P. Sondergeld, P. Quirke","doi":"10.1109/BIOVIS.2013.6664351","DOIUrl":"https://doi.org/10.1109/BIOVIS.2013.6664351","url":null,"abstract":"The scale of comparative genomics data frequently overwhelms current data visualization methods on conventional (desktop) displays. This paper describes two types of solution that take advantage of wall-sized high-resolution displays (WHirDs), which have orders of magnitude more display real estate (i.e., pixels) than desktop displays. The first allows users to view detailed graphics of copy number variation (CNV) that were output by existing software. A WHirD's resolution allowed a 10x increase in the granularity of bioinformatics output that was feasible for users to visually analyze, and this revealed a pattern that had previously been smoothed out from the underlying data. The second involved interactive visualization software that was innovative because it uses a music score metaphor to lay out CNV data, overcomes a perceptual distortion caused by amplification/deletion thresholds, uses filtering to reduce graphical data overload, and is the first comparative genomics visualization software that is designed to leverage a WHirD's real estate. In a field evaluation, a clinical user discovered a fundamental error in the way their data had been processed, and established confidence in the software by using it to `find' known genetic patterns in hepatitis C-driven hepatocellular cancer.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117096924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BIOVIS.2013.6664344
Stefan Nickels, D. Stöckel, Sabine C. Mueller, Hans-Peter Lenhof, A. Hildebrandt, Anna Katharina Dehof
Structural biology is based on an important observation: the function of a biomolecule is determined by its three-dimensional structure and its physico-chemical properties. Hence, visualization, modeling, and simulation of molecular structures and of their properties are crucial tools of the field. Typically, the graphical interfaces to molecular modeling packages are aimed at domain experts with significant experience and require an extensive learning period. But in many scenarios, such as teaching, presentations, and demonstrations, it would be highly preferable to have an intuitive environment for showcasing molecular functionality. Ideally, it should support simple preparation of the presentations as well as their convenient display. To keep the user interface simple and focused, the environment should be particularly adapted to the processing of molecular structures. Here, we present such a presentation framework, called PresentaBALL, which uses established web technology standards to provide a freely configurable browser-based interface into the extensive modeling and visualization capabilities of the Biochemical Algorithms Library (BALL). The web interface is embedded into BALL's graphical frontend BALLView, and provides complete, interactive access to the loaded molecular data. PresentaBALL enables researchers in biology with basic knowledge in HTML, JavaScript, or Python to easily setup academic tutorials, demonstrations, or scientific presentations and lectures with 3D structure content and interactive workflows. Owing to its flexible design, other modern forms of teaching and presentation, such as massive open online courses (MOOC) can also use PresentaBALL as their core component. PresentaBALL is licensed under the GNU Public License (GPL) and will be made available in BALL/BALLView, starting with the upcoming release (1.5).
{"title":"PresentaBALL — A powerful package for presentations and lessons in structural biology","authors":"Stefan Nickels, D. Stöckel, Sabine C. Mueller, Hans-Peter Lenhof, A. Hildebrandt, Anna Katharina Dehof","doi":"10.1109/BIOVIS.2013.6664344","DOIUrl":"https://doi.org/10.1109/BIOVIS.2013.6664344","url":null,"abstract":"Structural biology is based on an important observation: the function of a biomolecule is determined by its three-dimensional structure and its physico-chemical properties. Hence, visualization, modeling, and simulation of molecular structures and of their properties are crucial tools of the field. Typically, the graphical interfaces to molecular modeling packages are aimed at domain experts with significant experience and require an extensive learning period. But in many scenarios, such as teaching, presentations, and demonstrations, it would be highly preferable to have an intuitive environment for showcasing molecular functionality. Ideally, it should support simple preparation of the presentations as well as their convenient display. To keep the user interface simple and focused, the environment should be particularly adapted to the processing of molecular structures. Here, we present such a presentation framework, called PresentaBALL, which uses established web technology standards to provide a freely configurable browser-based interface into the extensive modeling and visualization capabilities of the Biochemical Algorithms Library (BALL). The web interface is embedded into BALL's graphical frontend BALLView, and provides complete, interactive access to the loaded molecular data. PresentaBALL enables researchers in biology with basic knowledge in HTML, JavaScript, or Python to easily setup academic tutorials, demonstrations, or scientific presentations and lectures with 3D structure content and interactive workflows. Owing to its flexible design, other modern forms of teaching and presentation, such as massive open online courses (MOOC) can also use PresentaBALL as their core component. PresentaBALL is licensed under the GNU Public License (GPL) and will be made available in BALL/BALLView, starting with the upcoming release (1.5).","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128303247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664353
J. Kennedy, Martin Graham, T. Paterson, A. Law
While some data cleaning tasks can be performed automatically, many more require expert human guidance to steer the cleaning process, especially if erroneous or unclean data is a product of relationships between entities. An example is pedigree genotype data: inheritance hierarchies in which the correctness of genotype data for any individual is judged on comparison to their relations' genotypes, as individuals should inherit DNA from their assumed ancestors. Thus, cleaning this data must consider the relationships between individuals; sometimes this means more data must be cleaned than first assumed, while in other situations it means errors across many individuals can be remedied by cleaning the data of a shared relation. Such judgements require a domain expert to hypothesise the effect changing particular data has on the wider data set. Using a visualization tool with the ability to undertake what-if interactions can assist a user in correctly cleaning such data. We achieve this by closely coupling an existing pedigree visualisation technique, VIPER, with a genotype cleaning algorithm, and then develop necessary extensions to the visualization to allow interactive data cleaning. A comparative user evaluation with biologists shows the advantages of this visualisation design over an existing cleaning tool and we discuss the challenges in the design of visual cleaning tools in which errors may be transitive.
{"title":"Visual cleaning of genotype data","authors":"J. Kennedy, Martin Graham, T. Paterson, A. Law","doi":"10.1109/BioVis.2013.6664353","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664353","url":null,"abstract":"While some data cleaning tasks can be performed automatically, many more require expert human guidance to steer the cleaning process, especially if erroneous or unclean data is a product of relationships between entities. An example is pedigree genotype data: inheritance hierarchies in which the correctness of genotype data for any individual is judged on comparison to their relations' genotypes, as individuals should inherit DNA from their assumed ancestors. Thus, cleaning this data must consider the relationships between individuals; sometimes this means more data must be cleaned than first assumed, while in other situations it means errors across many individuals can be remedied by cleaning the data of a shared relation. Such judgements require a domain expert to hypothesise the effect changing particular data has on the wider data set. Using a visualization tool with the ability to undertake what-if interactions can assist a user in correctly cleaning such data. We achieve this by closely coupling an existing pedigree visualisation technique, VIPER, with a genotype cleaning algorithm, and then develop necessary extensions to the visualization to allow interactive data cleaning. A comparative user evaluation with biologists shows the advantages of this visualisation design over an existing cleaning tool and we discuss the challenges in the design of visual cleaning tools in which errors may be transitive.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130998288","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664347
Orit Shaer, Consuelo Valdes, Sirui Liu, Kara Lu, Traci Haddock, Swapnil P Bhatia, D. Densmore, R. Kincaid
MoClo Planner is an interactive visualization system for collaborative bio-design, utilizing a multi-touch interactive surface. The system integrates the information gathering, design, and specification of complex synthetic biological constructs using the Modular Cloning (MoClo) assembly method. Modular Cloning is a hierarchical DNA construction method that allows for the assembly of multi-part constructs from a library of biological parts in a one-pot reaction. This cutting-edge method facilitates and expedites the assembly of complex biological designs. However, it is an intricate multi-step process, which to date, has not been adequately supported by existing bio-design tools. Novel visual tools are needed in order to make MoClo more tractable and accessible to a broad range of users, to facilitate a less error prone bio-design process, and to improve workflow. MoClo Planner is a result of a participatory and user-centered design process, which included close collaboration with domain experts. Using multi-touch interactions and a rich graphical interface, the system accelerates the MoClo learning process, and reduces design time and errors. In this paper, we present user requirements and describe the design, implementation, and evaluation of MoClo Planner.
{"title":"MoClo planner: Interactive visualization for Modular Cloning bio-design","authors":"Orit Shaer, Consuelo Valdes, Sirui Liu, Kara Lu, Traci Haddock, Swapnil P Bhatia, D. Densmore, R. Kincaid","doi":"10.1109/BioVis.2013.6664347","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664347","url":null,"abstract":"MoClo Planner is an interactive visualization system for collaborative bio-design, utilizing a multi-touch interactive surface. The system integrates the information gathering, design, and specification of complex synthetic biological constructs using the Modular Cloning (MoClo) assembly method. Modular Cloning is a hierarchical DNA construction method that allows for the assembly of multi-part constructs from a library of biological parts in a one-pot reaction. This cutting-edge method facilitates and expedites the assembly of complex biological designs. However, it is an intricate multi-step process, which to date, has not been adequately supported by existing bio-design tools. Novel visual tools are needed in order to make MoClo more tractable and accessible to a broad range of users, to facilitate a less error prone bio-design process, and to improve workflow. MoClo Planner is a result of a participatory and user-centered design process, which included close collaboration with domain experts. Using multi-touch interactions and a rich graphical interface, the system accelerates the MoClo learning process, and reduces design time and errors. In this paper, we present user requirements and describe the design, implementation, and evaluation of MoClo Planner.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114440317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664349
J. Sorger, K. Bühler, F. Schulze, Tianxiao Liu, B. Dickson
Neuroscientists study the function of neural circuits in the brain of the common fruit fly Drosophila melanogaster to discover how complex behavior is generated. To establish models of neural information processing, knowledge about potential connections between individual neurons is required. Connections can occur when the arborizations of two neurons overlap. Judging connectivity by analyzing overlaps using traditional volumetric visualization is difficult since the examined objects occlude each other. A more abstract form of representation is therefore desirable. In collaboration with a group of neuroscientists, we designed and implemented neuroMap, an interactive two-dimensional graph that renders the brain and its interconnections in the form of a circuit-style wiring diagram. neuroMap provides a clearly structured overview of all possible connections between neurons and offers means for interactive exploration of the underlying neuronal database. In this paper, we discuss the design decisions that formed neuroMap and evaluate its application in discussions with the scientists.
{"title":"neuroMAP — Interactive graph-visualization of the fruit fly's neural circuit","authors":"J. Sorger, K. Bühler, F. Schulze, Tianxiao Liu, B. Dickson","doi":"10.1109/BioVis.2013.6664349","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664349","url":null,"abstract":"Neuroscientists study the function of neural circuits in the brain of the common fruit fly Drosophila melanogaster to discover how complex behavior is generated. To establish models of neural information processing, knowledge about potential connections between individual neurons is required. Connections can occur when the arborizations of two neurons overlap. Judging connectivity by analyzing overlaps using traditional volumetric visualization is difficult since the examined objects occlude each other. A more abstract form of representation is therefore desirable. In collaboration with a group of neuroscientists, we designed and implemented neuroMap, an interactive two-dimensional graph that renders the brain and its interconnections in the form of a circuit-style wiring diagram. neuroMap provides a clearly structured overview of all possible connections between neurons and offers means for interactive exploration of the underlying neuronal database. In this paper, we discuss the design decisions that formed neuroMap and evaluate its application in discussions with the scientists.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"163 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123286878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BIOVIS.2013.6664340
Çağatay Demiralp, Eric J. Hayden, Jeff Hammerbacher, Jeffrey Heer
In vitro selection and evolution is a powerful method for discovering RNA molecules based on their binding and catalysis properties. It has important applications to the study of genetic variation and molecular evolution. However, the resulting RNA sequences form a large, high-dimensional space and biologists lack adequate tools to explore and interpret these sequences. We present invis, the first visual analysis tool to facilitate exploration of in vitro selection sequence spaces. invis introduces a novel configuration of coordinated views that enables simultaneous inspection of global projections of sequence data alongside local regions of selected dimensions and sequence clusters. It allows scientists to isolate related sequences for further data analysis, compare sequence populations over varying conditions, filter sequences based on their similarities, and visualize likely pathways of genetic evolution. User feedback indicates that invis enables effective exploration of in vitro RNA selection sequences.
{"title":"invis: Exploring high-dimensional RNA sequences from in vitro selection","authors":"Çağatay Demiralp, Eric J. Hayden, Jeff Hammerbacher, Jeffrey Heer","doi":"10.1109/BIOVIS.2013.6664340","DOIUrl":"https://doi.org/10.1109/BIOVIS.2013.6664340","url":null,"abstract":"In vitro selection and evolution is a powerful method for discovering RNA molecules based on their binding and catalysis properties. It has important applications to the study of genetic variation and molecular evolution. However, the resulting RNA sequences form a large, high-dimensional space and biologists lack adequate tools to explore and interpret these sequences. We present invis, the first visual analysis tool to facilitate exploration of in vitro selection sequence spaces. invis introduces a novel configuration of coordinated views that enables simultaneous inspection of global projections of sequence data alongside local regions of selected dimensions and sequence clusters. It allows scientists to isolate related sequences for further data analysis, compare sequence populations over varying conditions, filter sequences based on their similarities, and visualize likely pathways of genetic evolution. User feedback indicates that invis enables effective exploration of in vitro RNA selection sequences.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128747629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664346
Kenneth Sabir, C. Stolte, B. Tabor, S. O’Donoghue
Three-dimensional (3D) molecular graphic systems are widely used in the life sciences, both for research and communication. These systems need to enable a rich set of 3D operations, including three-axis rotation and translation, selection of parts of macromolecules, and the ability to redefine the center of rotation. As a result, graphical interfaces for these systems typically require users to learn complex keyboard and mouse combinations. This can be a significant barrier for new or occasional users, and even for experts, precise control of 3D molecular structures can be challenging. To help address these challenges, we developed the Molecular Control Toolkit to support multiple consumer gesture and voice recognition devices, and provide an API that allows adaption to multiple molecular graphics systems. The toolkit allows intuitive control, almost as if users are directly manipulating 3D objects in their hands. We applied the toolkit to the Kinect and Leap Motion devices, and to the Aquaria molecular graphics system. We did a pilot user study with 18 life scientists to test the resulting system in different scenarios. Overall, users gave quite favorable ratings to using the Kinect and Leap Motion gesture devices to control molecular graphics, even though these devices initially proved less efficient for common 3D control tasks, compared to the more familiar mouse/keyboard. To our knowledge, this is the first toolkit for macromolecular graphics that supports multiple devices with a set of controls sufficiently rich to be useful in the day-to-day work of a broad range of life scientists. The Molecular Control Toolkit and Aquaria can be accessed at http://aquaria.ws.
{"title":"The Molecular Control Toolkit: Controlling 3D molecular graphics via gesture and voice","authors":"Kenneth Sabir, C. Stolte, B. Tabor, S. O’Donoghue","doi":"10.1109/BioVis.2013.6664346","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664346","url":null,"abstract":"Three-dimensional (3D) molecular graphic systems are widely used in the life sciences, both for research and communication. These systems need to enable a rich set of 3D operations, including three-axis rotation and translation, selection of parts of macromolecules, and the ability to redefine the center of rotation. As a result, graphical interfaces for these systems typically require users to learn complex keyboard and mouse combinations. This can be a significant barrier for new or occasional users, and even for experts, precise control of 3D molecular structures can be challenging. To help address these challenges, we developed the Molecular Control Toolkit to support multiple consumer gesture and voice recognition devices, and provide an API that allows adaption to multiple molecular graphics systems. The toolkit allows intuitive control, almost as if users are directly manipulating 3D objects in their hands. We applied the toolkit to the Kinect and Leap Motion devices, and to the Aquaria molecular graphics system. We did a pilot user study with 18 life scientists to test the resulting system in different scenarios. Overall, users gave quite favorable ratings to using the Kinect and Leap Motion gesture devices to control molecular graphics, even though these devices initially proved less efficient for common 3D control tasks, compared to the more familiar mouse/keyboard. To our knowledge, this is the first toolkit for macromolecular graphics that supports multiple devices with a set of controls sufficiently rich to be useful in the day-to-day work of a broad range of life scientists. The Molecular Control Toolkit and Aquaria can be accessed at http://aquaria.ws.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-11-14DOI: 10.1109/BioVis.2013.6664343
Doyoung Park, Desiree Jones, N. Moldovan, R. Machiraju, T. Pécot
Polymerized actin-based cytoskeletal structures provide the cells with shape, resilience and dynamics. A mechanistic understanding of actin-based structures is crucial for finding solutions to practical problems occurring in tissue engineering constructs that require the interaction of cells with materials. In this regard, the first step is to detect and quantify actin-based structures in 3D cellular ensembles. In this work, we propose visual-analytic tools to delineate specific structures involving F-actin in cells. Concave actin bundles (CABs) often occur in hybrid cell-seeded fibrillar scaffolds and seem to envelope the fibers, as a possible mechanism of stable attachment. There is much uncertainty that accompanies the detection and the identification of fibers. Our tools rely on well-known algorithms of image analysis. We first delineate fibers by employing an adaptive min-cut-max-flow algorithm. Then, from the extremities of the segmented fibers, a template matching and a fiber tracking algorithm is applied to more precisely characterize the fibers in the image. CABs that surround the scaffold fibers transversally are located by observing their radial distribution around the nearby templates in focus. Finally, we visually examine candidate templates that possibly contain CABs and further determine if candidate CABs are indeed legitimate. It can be unequivocally stated that in the absence of the proposed visual analytic tools, the detection of CABs is intractable tasks.
{"title":"Robust detection and visualization of cytoskeletal structures in fibrillar scaffolds from 3-dimensional confocal image","authors":"Doyoung Park, Desiree Jones, N. Moldovan, R. Machiraju, T. Pécot","doi":"10.1109/BioVis.2013.6664343","DOIUrl":"https://doi.org/10.1109/BioVis.2013.6664343","url":null,"abstract":"Polymerized actin-based cytoskeletal structures provide the cells with shape, resilience and dynamics. A mechanistic understanding of actin-based structures is crucial for finding solutions to practical problems occurring in tissue engineering constructs that require the interaction of cells with materials. In this regard, the first step is to detect and quantify actin-based structures in 3D cellular ensembles. In this work, we propose visual-analytic tools to delineate specific structures involving F-actin in cells. Concave actin bundles (CABs) often occur in hybrid cell-seeded fibrillar scaffolds and seem to envelope the fibers, as a possible mechanism of stable attachment. There is much uncertainty that accompanies the detection and the identification of fibers. Our tools rely on well-known algorithms of image analysis. We first delineate fibers by employing an adaptive min-cut-max-flow algorithm. Then, from the extremities of the segmented fibers, a template matching and a fiber tracking algorithm is applied to more precisely characterize the fibers in the image. CABs that surround the scaffold fibers transversally are located by observing their radial distribution around the nearby templates in focus. Finally, we visually examine candidate templates that possibly contain CABs and further determine if candidate CABs are indeed legitimate. It can be unequivocally stated that in the absence of the proposed visual analytic tools, the detection of CABs is intractable tasks.","PeriodicalId":356842,"journal":{"name":"2013 IEEE Symposium on Biological Data Visualization (BioVis)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114931964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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