scholarly journals Comparative Study of Computational Methods for Reconstructing Genetic Networks of Cancer-Related Pathways

2014 ◽  
Vol 13s2 ◽  
pp. CIN.S13781
Author(s):  
Nafiseh Sedaghat ◽  
Takumi Saegusa ◽  
Timothy Randolph ◽  
Ali Shojaie
Keyword(s):  
Biological Networks ◽  
Genetic Interaction ◽  
Empirical Evaluation ◽  
Network Reconstruction ◽  
Data Types ◽  
Reconstruction Methods ◽  
Cancer Initiation ◽  
Diverse Data ◽  
Substantial Heterogeneity ◽  
Insight Into

Network reconstruction is an important yet challenging task in systems biology. While many methods have been recently proposed for reconstructing biological networks from diverse data types, properties of estimated networks and differences between reconstruction methods are not well understood. In this paper, we conduct a comprehensive empirical evaluation of seven existing network reconstruction methods, by comparing the estimated networks with different sparsity levels for both normal and tumor samples. The results suggest substantial heterogeneity in networks reconstructed using different reconstruction methods. Our findings also provide evidence for significant differences between networks of normal and tumor samples, even after accounting for the considerable variability in structures of networks estimated using different reconstruction methods. These differences can offer new insight into changes in mechanisms of genetic interaction associated with cancer initiation and progression.

Gotta catch ‘em all: the microscale quest to understand cancer biology

2016 ◽  
Vol 8 (12) ◽  
pp. 1203-1207 ◽  
Author(s):  
Zhenwei Ma ◽  
Christopher Moraes
Keyword(s):  
Cancer Biology ◽  
Recent Advances ◽  
Cancer Initiation ◽  
Insight Into

We highlight recent advances in the innovative use of microscale engineered technologies to gain new insight into the integrative biophysical mechanisms that drive cancer initiation and progression.

scholarly journals Combining Multiple Organizational-level Databases: An Empirical Evaluation of Different Matching Methods

2021 ◽  
pp. 004912412098618
Author(s):  
Tim de Leeuw ◽  
Steffen Keijl
Keyword(s):  
Empirical Evaluation ◽  
Organizational Level ◽  
Random Errors ◽  
Data Set ◽  
Future Studies ◽  
Matching Methods ◽  
Matching Process ◽  
Significant Relationships ◽  
Research Findings ◽  
Insight Into

Although multiple organizational-level databases are frequently combined into one data set, there is no overview of the matching methods (MMs) that are utilized because the vast majority of studies does not report how this was done. Furthermore, it is unclear what the differences are between the utilized methods, and it is unclear whether research findings might be influenced by the utilized method. This article describes four commonly used methods for matching databases and potential issues. An empirical comparison of those methods used to combine regularly used organizational-level databases reveals large differences in the number of observations obtained. Furthermore, empirical analyses of these different methods reveal that several of them produce both systematic and random errors. These errors can result in erroneous estimations of regression coefficients in terms of direction and/or size as well as an issue where truly significant relationships might be found to be insignificant. This shows that research findings can be influenced by the MM used, which would argue in favor of the establishment of a preferred method as well as more transparency on the utilized method in future studies. This article provides insight into the matching process and methods, suggests a preferred method, and should aid researchers, reviewers, and editors with both combining multiple databases and describing and assessing them.

The award of medals by the President, Sir Andrew Huxley, O.M., at the Anniversary Meeting, 30 November 1985

1986 ◽  
Vol 405 (1829) ◽  
pp. 181-184
Keyword(s):  
Electron Microscopy ◽  
Image Reconstruction ◽  
Coat Protein ◽  
Tobacco Mosaic Virus ◽  
Mosaic Virus ◽  
Deep Insight ◽  
Living Matter ◽  
Fourier Image ◽  
Reconstruction Methods ◽  
Insight Into

The Copley Medal is awarded to Dr A. Klug, F. R. S., in recognition of his outstanding contributions to our understanding of complex biological structures and the methods used for determining them. Together with D. Kaspar, Klug developed a theory that predicted the arrangement of sub-units in the protein shells of spherical viruses. This theory brought order and understanding into a confused field ; nearly all the observed structures of small spherical viruses, many of them elucidated by Klug and his collaborators, are consistent with it. After more than 20 years’ work on tobacco mosaic virus Klug and his colleagues solved the structure of its coat protein in atomic detail. They also elucidated the mechanisms by which the helical virus particle assembles itself from its RNA and its 2130 protein sub-units. Recently his group succeeded in crystallizing chromatin, and solved its structure at a resolution sufficient to see the double-helical DNA coiled around the spool of histone. Many of Klug’s successes were made possible by his introduction of Fourier image reconstruction methods into electron microscopy. Klug’s work is characterized by deep insight into the physics of diffraction and image formation and the intricate geometry of living matter.

scholarly journals Systematic characterization and genetic interaction analysis of adhesins in Candida albicans virulence

2020 ◽  
Author(s):  
Sierra Rosiana ◽  
Liyang Zhang ◽  
Grace H. Kim ◽  
Alexey V. Revtovich ◽  
Arjun Sukumaran ◽  
...  
Keyword(s):  
Candida Albicans ◽  
Genetic Interaction ◽  
Interaction Analysis ◽  
Genetic Interactions ◽  
Fungal Virulence ◽  
C Elegans ◽  
Adhesin Proteins ◽  
Insight Into

AbstractCandida albicans is a microbial fungus that exists as a commensal member of the human microbiome and an opportunistic pathogen. Cell surface-associated adhesin proteins play a crucial role in C. albicans’ ability to undergo cellular morphogenesis, develop robust biofilms, colonize, and cause infection in a host. However, a comprehensive analysis of the role and relationships between these adhesins has not been explored. We previously established a CRISPR-based platform for efficient generation of single- and double-gene deletions in C. albicans, which was used to construct a library of 144 mutants, comprising 12 unique adhesin genes deleted singly, or in every possible combination of double deletions. Here, we exploit this adhesin mutant library to explore the role of adhesin proteins in C. albicans virulence. We perform a comprehensive, high-throughput screen of this library, using Caenorhabditis elegans as a simplified model host system, which identified mutants critical for virulence and significant genetic interactions. We perform follow-up analysis to assess the ability of high- and low-virulence strains to undergo cellular morphogenesis and form biofilms in vitro, as well as to colonize the C. elegans host. We further perform genetic interaction analysis to identify novel significant negative genetic interactions between adhesin mutants, whereby combinatorial perturbation of these genes significantly impairs virulence, more than expected based on virulence of the single mutant constituent strains. Together, this yields important new insight into the role of adhesins, singly and in combinations, in mediating diverse facets of virulence of this critical fungal pathogen.SummaryCandida albicans is a human fungal pathogen and cause of life-threatening systemic infections. Cell surface-associated adhesins play a central role in this pathogen’s ability to establish infection. Here, we provide a comprehensive analysis of adhesin factors, and their role in fungal virulence. Exploiting a high-throughput workflow, we screened an adhesin mutant library using C. elegans as a simple model host, and identified mutants and genetic interactions involved in virulence. We found that adhesin mutants are impaired in in vitro pathogenicity, irrespective of their virulence. Together, this work provides new insight into the role of adhesin factors in mediating fungal virulence.

scholarly journals Brain Tumor Discovery Using Image Preprocessing

2020 ◽  
Vol 11 (4) ◽  
pp. 6870-6875
Author(s):  
Prem Jacob T ◽  
Polakam Sukanya ◽  
Thatiparthi Madhavi
Keyword(s):  
Big Data Analytics ◽  
Malignant Growth ◽  
Data Types ◽  
Mri Scan ◽  
Tree Disease ◽  
Cancer Prediction ◽  
Wired Communication ◽  
The Brain ◽  
Highlight Extraction ◽  
Insight Into

The segmentation of attractive reverberation images assumes a critical job in therapeutic fields since it removes the required territory from the picture. Generally, there is no unique methodology for the segmentation of the picture. Tumour division from MRI information is a critical tedious manual undertaking performed by therapeutic specialists. In this paper, the Brain Cancer prediction System has been detailed. The framework utilizes PC based methods to recognize tumor squares and classify the tumour utilizing Artificial Neural Network. The picture preparing strategies, for example, histogram evening out, picture division, picture improvement, and highlight extraction, have been produced for the location of the cerebrum tumor in the MRI pictures of the malignant growth Detected patients. This paper focuses around another and exceptionally acclaimed algorithm for mind tumor division of MRI scan image by ANN and SVM algorithms to analyze precisely the locale of malignant growth as a result of its straightforwardness and computational proficiency. The MATLAB output will be shown in pc and furthermore observe the yield to insert framework utilizing wired communication. To the best of our insight into the zone of therapeutic big data analytics, none of the current work concentrated on the two data types. Contrasted with a few runs of the typical algorithms, the computation precision of our proposed algorithm achieves 94.8% with an assembly speed, which is quicker than that of the Decision tree disease hazard prediction.

scholarly journals Linking Norms, Ratings, and Relations of Words and Concepts Across Multiple Language Varieties

2020 ◽  
Author(s):  
Annika Tjuka ◽  
Robert Forkel ◽  
Johann-Mattis List
Keyword(s):  
Web Application ◽  
Age Of Acquisition ◽  
Data Curation ◽  
Data Sets ◽  
Data Types ◽  
Word Meanings ◽  
Language Varieties ◽  
Diverse Data ◽  
Multiple Languages ◽  
Word Frequencies

Psychologists and linguists have collected a great diversity of data for word and concept properties. In psychology, many studies accumulate norms and ratings such as word frequencies or age-of-acquisition often for a large number of words. Linguistics, on the other hand, provides valuable insights into relations of word meanings. We present a collection of those data sets for norms, ratings, and relations that cover different languages: ‘NoRaRe.’ To enable a comparison between the diverse data types, we established workflows that facilitate the expansion of the database. A web application allows convenient access to the data (https://digling.org/norare/). Furthermore, a software API ensures consistent data curation by providing tests to validate the data sets. The NoRaRe collection is linked to the database curated by the Concepticon project (https://concepticon.clld.org) which offers a reference catalog of unified concept sets. The link between words in the data sets and the Concepticon concept sets makes a cross-linguistic comparison possible. In three case studies, we test the validity of our approach, the accuracy of our workflow, and the applicability of our database. The results indicate that the NoRaRe database can be applied for the study of word properties across multiple languages. The data can be used by psychologists and linguists to benefit from the knowledge rooted in both research disciplines.

The Digital Earth Viewer: A new visualization approach for geospatial time series data

2021 ◽  
Author(s):  
Valentin Buck ◽  
Flemming Stäbler ◽  
Everardo Gonzalez ◽  
Jens Greinert
Keyword(s):  
Time Series Data ◽  
Environmental Data ◽  
Series Data ◽  
Multiple Sources ◽  
Data Types ◽  
New Approach ◽  
Digital Earth ◽  
Spatio Temporal ◽  
Diverse Data

<p>The study of the earth’s systems depends on a large amount of observations from homogeneous sources, which are usually scattered around time and space and are tightly intercorrelated to each other. The understanding of said systems depends on the ability to access diverse data types and contextualize them in a global setting suitable for their exploration. While the collection of environmental data has seen an enormous increase over the last couple of decades, the development of software solutions necessary to integrate observations across disciplines seems to be lagging behind. To deal with this issue, we developed the Digital Earth Viewer: a new program to access, combine, and display geospatial data from multiple sources over time.</p><p>Choosing a new approach, the software displays space in true 3D and treats time and time ranges as true dimensions. This allows users to navigate observations across spatio-temporal scales and combine data sources with each other as well as with meta-properties such as quality flags. In this way, the Digital Earth Viewer supports the generation of insight from data and the identification of observational gaps across compartments.</p><p>Developed as a hybrid application, it may be used both in-situ as a local installation to explore and contextualize new data, as well as in a hosted context to present curated data to a wider audience.</p><p>In this work, we present this software to the community, show its strengths and weaknesses, give insight into the development process and talk about extending and adapting the software to custom usecases.</p>

Enterprise Data Lake Management in Business Intelligence and Analytics

2021 ◽  
pp. 92-113
Author(s):  
Mohammad Kamel Daradkeh
Keyword(s):  
Business Intelligence ◽  
Lake Management ◽  
Reference Architecture ◽  
Data Types ◽  
Research Gaps ◽  
Effective Implementation ◽  
Integration Strategy ◽  
Governance Strategy ◽  
Diverse Data ◽  
Modelling Methods

The data lake has recently emerged as a scalable architecture for storing, integrating, and analyzing massive data volumes characterized by diverse data types, structures, and sources. While the data lake plays a key role in unifying business intelligence, analytics, and data mining in an enterprise, effective implementation of an enterprise-wide data lake for business intelligence and analytics integration is associated with a variety of practical challenges. In this chapter, concrete analytics projects of a globally industrial enterprise are used to identify existing practical challenges and drive requirements for enterprise data lakes. These requirements are compared with the extant literature on data lake technologies and management to identify research gaps in analytics practice. The comparison shows that there are five major research gaps: 1) unclear data modelling methods, 2) missing data lake reference architecture, 3) incomplete metadata management strategy, 4) incomplete data lake governance strategy, and 5) missing holistic implementation and integration strategy.

Intra-arterial chemotherapy for retinoblastoma: an updated systematic review and meta-analysis

2019 ◽  
Vol 11 (12) ◽  
pp. 1266-1272 ◽  
Author(s):  
Krishnan Ravindran ◽  
Lauren A Dalvin ◽  
Jose S Pulido ◽  
Waleed Brinjikji
Keyword(s):  
Metastatic Disease ◽  
Meta Analysis ◽  
Inclusion Criteria ◽  
First Line ◽  
Short Term ◽  
Systemic Complications ◽  
Substantial Heterogeneity ◽  
Insight Into

Background and purposeIntra-arterial chemotherapy for retinoblastoma has been adopted as a first-line treatment option by numerous tertiary centers. The effect of intra-arterial chemotherapy on future rates of metastatic disease as well as on globe salvage in advanced eyes remains relatively unknown.MethodsA search of PubMED, MEDLINE, EMBASE, and Web of Science electronic databases was conducted from inception until January 2019 for studies with a minimum of 10 patients reporting outcomes and complications following intra-arterial chemotherapy for retinoblastoma.ResultsA total of 20 studies met the inclusion criteria for analysis, comprising 873 patients and 1467 eyes. Only one study was comparative; there was substantial heterogeneity in reported outcomes and several overlapping patient cohorts that were published. Across all studies, 174 of 1467 eyes were enucleated (11.8%). Metastatic disease occurred in 8 of 513 patients (1.6%). Globe salvage was achieved in 318 of 906 (35.6%) cases of advanced retinoblastoma. The most common ocular complication was retinal detachment, occurring in 23% of eyes, and the most common systemic complications were transient fever and nausea/vomiting.ConclusionsThere is a paucity of higher-level evidence with adequate follow-up surrounding the long-term safety of intra-arterial chemotherapy and effect on metastasis in retinoblastoma. Studies to date have been limited by short-term follow-up. Longitudinal prospective studies could provide greater insight into the ability of intra-arterial chemotherapy to reduce the risk of retinoblastoma metastasis.

3D data visualization: The advantages of volume graphics and big data to support geologic interpretation

2015 ◽  
Vol 3 (3) ◽  
pp. SX29-SX39 ◽  
Author(s):  
Carl Byers ◽  
Andrew Woo
Keyword(s):  
Big Data ◽  
Case Studies ◽  
Data Visualization ◽  
3D Visualization ◽  
Data Types ◽  
Volume Graphics ◽  
3D Data ◽  
Geologic Interpretation ◽  
Diverse Data

The ability to integrate diverse data types from multiple live and simulated sources, manipulate them dynamically, and deploy them in integrated, visual formats and in mobile settings provides significant advantages. We have reviewed some of the benefits of volume graphics and the use of big data in the context of 3D visualization case studies, in which inherent features, such as representation efficiencies, dynamic modifications, cross sectioning, and others, could improve interpretation processes and workflows.

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