scholarly journals Toward synthesizing our knowledge of morphology: using ontologies and machine reasoning to extract presence/absence evolutionary phenotypes across studies

2015 ◽  
Author(s):  
T. Alexander Dececchi ◽  
James P Balhoff ◽  
Hilmar Lapp ◽  
Paula M Mabee
Keyword(s):  
Formal Semantics ◽  
Model Organism ◽  
Future Research ◽  
Data Provenance ◽  
Character State ◽  
Phenotypic Data ◽  
Large Numbers ◽  
Molecular Databases ◽  
Variable Character ◽  
Character Matrix

The reality of larger and larger molecular databases and the need to integrate data scalably have presented a major challenge for the use of phenotypic data. Morphology is currently primarily described in discrete publications, entrenched in non-computer readable text, and requires enormous investments of time and resources to integrate across large numbers of taxa and studies. Here we present a new methodology, using ontology-based reasoning systems working with the Phenoscape Knowledgebase (KB), to automatically integrate large amounts of evolutionary character state descriptions into a synthetic character matrix of neomorphic (presence/absence) data. Using the KB, which includes more than 55 studies of sarcopterygian taxa, we generated a synthetic supermatrix of 1051 variable characters scored for 639 taxa resulting in over 145,000 populated cells. Of these characters, over 76% were made variable through the addition of inferred presence/absence states derived by machine reasoning over the formal semantics of the source ontologies. Inferred data reduced the missing data in the variable character-subset from 98.5% to 78.2%. Machine reasoning also enables the isolation of conflicts in the data, i.e., cells where both presence and absence are indicated; reports regarding conflicting data provenance can be generated automatically. Further, reasoning enables quantification and new visualizations of the data, here for example, allowing identification of character space that has been undersampled across the fin to limb transition. The approach and methods demonstrated here to compute synthetic presence/absence supermatrices are applicable to any taxonomic and phenotypic slice across the tree of life, providing the data are semantically annotated. Because such data can also be linked to model organism genetics through computational scoring of phenotypic similarity, they open a rich set of future research questions into phenotype to genome relationships.

scholarly journals Toward synthesizing our knowledge of morphology: using ontologies and machine reasoning to extract presence/absence evolutionary phenotypes across studies

2015 ◽  
Author(s):  
T. Alexander Dececchi ◽  
James P Balhoff ◽  
Hilmar Lapp ◽  
Paula M Mabee
Keyword(s):  
Formal Semantics ◽  
Model Organism ◽  
Future Research ◽  
Data Provenance ◽  
Character State ◽  
Phenotypic Data ◽  
Large Numbers ◽  
Molecular Databases ◽  
Variable Character ◽  
Character Matrix

The reality of larger and larger molecular databases and the need to integrate data scalably have presented a major challenge for the use of phenotypic data. Morphology is currently primarily described in discrete publications, entrenched in non-computer readable text, and requires enormous investments of time and resources to integrate across large numbers of taxa and studies. Here we present a new methodology, using ontology-based reasoning systems working with the Phenoscape Knowledgebase (KB), to automatically integrate large amounts of evolutionary character state descriptions into a synthetic character matrix of neomorphic (presence/absence) data. Using the KB, which includes more than 55 studies of sarcopterygian taxa, we generated a synthetic supermatrix of 1051 variable characters scored for 639 taxa resulting in over 145,000 populated cells. Of these characters, over 76% were made variable through the addition of inferred presence/absence states derived by machine reasoning over the formal semantics of the source ontologies. Inferred data reduced the missing data in the variable character-subset from 98.5% to 78.2%. Machine reasoning also enables the isolation of conflicts in the data, i.e., cells where both presence and absence are indicated; reports regarding conflicting data provenance can be generated automatically. Further, reasoning enables quantification and new visualizations of the data, here for example, allowing identification of character space that has been undersampled across the fin to limb transition. The approach and methods demonstrated here to compute synthetic presence/absence supermatrices are applicable to any taxonomic and phenotypic slice across the tree of life, providing the data are semantically annotated. Because such data can also be linked to model organism genetics through computational scoring of phenotypic similarity, they open a rich set of future research questions into phenotype to genome relationships.

scholarly journals The Evolution of Life Modes in Stictidaceae, with Three Novel Taxa

2021 ◽  
Vol 7 (2) ◽  
pp. 105
Author(s):  
Vinodhini Thiyagaraja ◽  
Robert Lücking ◽  
Damien Ertz ◽  
Samantha C. Karunarathna ◽  
Dhanushka N. Wanasinghe ◽  
...  
Keyword(s):  
New Species ◽  
Large Scale ◽  
Sequence Data ◽  
Large Subunit ◽  
Monte Carlo Sampling ◽  
Small Subunit ◽  
Sensu Stricto ◽  
Internal Transcribed Spacers ◽  
Character State ◽  
Phenotypic Data

Ostropales sensu lato is a large group comprising both lichenized and non-lichenized fungi, with several lineages expressing optional lichenization where individuals of the same fungal species exhibit either saprotrophic or lichenized lifestyles depending on the substrate (bark or wood). Greatly variable phenotypic characteristics and large-scale phylogenies have led to frequent changes in the taxonomic circumscription of this order. Ostropales sensu lato is currently split into Graphidales, Gyalectales, Odontotrematales, Ostropales sensu stricto, and Thelenellales. Ostropales sensu stricto is now confined to the family Stictidaceae, which includes a large number of species that are poorly known, since they usually have small fruiting bodies that are rarely collected, and thus, their taxonomy remains partly unresolved. Here, we introduce a new genus Ostropomyces to accommodate a novel lineage related to Ostropa, which is composed of two new species, as well as a new species of Sphaeropezia, S. shangrilaensis. Maximum likelihood and Bayesian inference analyses of mitochondrial small subunit spacers (mtSSU), large subunit nuclear rDNA (LSU), and internal transcribed spacers (ITS) sequence data, together with phenotypic data documented by detailed morphological and anatomical analyses, support the taxonomic affinity of the new taxa in Stictidaceae. Ancestral character state analysis did not resolve the ancestral nutritional status of Stictidaceae with confidence using Bayes traits, but a saprotrophic ancestor was indicated as most likely in a Bayesian binary Markov Chain Monte Carlo sampling (MCMC) approach. Frequent switching in nutritional modes between lineages suggests that lifestyle transition played an important role in the evolution of this family.

scholarly journals Proof-of-PUF Enabled Blockchain: Concurrent Data and Device Security for Internet-of-Energy

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 28
Author(s):  
Rameez Asif ◽  
Kinan Ghanem ◽  
James Irvine
Keyword(s):  
Hybrid Approach ◽  
Future Research ◽  
Data Provenance ◽  
Data Generation ◽  
Cyber Attack ◽  
Design Development ◽  
Seamless Integration ◽  
Device Identification ◽  
Physical Unclonable Functions ◽  
History Of

A detailed review on the technological aspects of Blockchain and Physical Unclonable Functions (PUFs) is presented in this article. It stipulates an emerging concept of Blockchain that integrates hardware security primitives via PUFs to solve bandwidth, integration, scalability, latency, and energy requirements for the Internet-of-Energy (IoE) systems. This hybrid approach, hereinafter termed as PUFChain, provides device and data provenance which records data origins, history of data generation and processing, and clone-proof device identification and authentication, thus possible to track the sources and reasons of any cyber attack. In addition to this, we review the key areas of design, development, and implementation, which will give us the insight on seamless integration with legacy IoE systems, reliability, cyber resilience, and future research challenges.

ISOLATION AND IDENTIFICATION OF RHIZOSPHERIC BACTERIA ASSOCIATED WITH LEMONGRASS FOR POTENTIAL BIOREMEDIATION

2015 ◽  
Vol 77 (24) ◽  
Author(s):  
Najwa Husna Sanusi ◽  
Phang Ing Chia ◽  
Noor Faizul Hadry Nordin
Keyword(s):  
Future Research ◽  
Rrna Gene ◽  
Public Attention ◽  
Isolation And Identification ◽  
Severe Problem ◽  
Rhizospheric Bacteria ◽  
Large Numbers ◽  
Degrading Bacteria ◽  
Cleaner Technology ◽  
Remediation Process

Contamination of soil and groundwater pollution is a severe problem, has been attracting considerable public attention over the last decades. With the demand for green and cleaner technology for remediation process, there is an increased interest in moving away from conventional technologies towards bioremediation technologies. Rhizospheric zone is a suitable place for harboring bacteria that are capable to utilize chemical compounds which will be used either to facilitate growth of bacteria or the host plants. Identification of the specific microbial members should allow for better strategies to enhance biodegradation. This study aimed to isolate and identify the rhizospheric associated microbes of lemongrass (Cymbopogon citratus), a plant that commonly available in South East Asia, which could be used in future research on degradation studies of dibenzofuran. This probably is due to their ability to harbor large numbers of bacteria on their highly branched root systems. A total of 68 strains of dibenzofuran (DF)- degrading bacteria isolated from the rhizospheric soil of lemon grass from 2 different unpolluted sites were characterized. The isolates showed the ability to utilize dibenzofuran as the sole carbon and energy source up to 40 ppm. Identification of the isolates based on 16S rRNA gene sequence assigned them as members of the phyla Proteobacteria and Firmicutes, among which those of the genera, Proteobacteria were most abundant. The presented results indicated the potential of these bacterial isolates in bioremediation of dibenzofuran-contaminated soil.

scholarly journals The C. elegans Hypertonic Stress Response: Big Insights from Shrinking Worms

2020 ◽  
Vol 55 (S1) ◽  
pp. 89-105
Keyword(s):  
Stress Response ◽  
Cell Volume ◽  
Molecular Mechanisms ◽  
Model Organism ◽  
Future Research ◽  
Transcriptional Level ◽  
Molecular Signaling ◽  
Hypertonic Stress ◽  
Macromolecular Assemblies ◽  
C Elegans

Cell volume is one of the most aggressively defended physiological set points in biology. Changes in intracellular ion and water concentrations, which are induced by changes in metabolism or environmental exposures, disrupt protein folding, enzymatic activity, and macromolecular assemblies. To counter these challenges, cells and organisms have evolved multifaceted, evolutionarily conserved molecular mechanisms to restore cell volume and repair stress induced damage. However, many unanswered questions remain regarding the nature of cell volume 'sensing' as well as the molecular signaling pathways involved in activating physiological response mechanisms. Unbiased genetic screening in the model organism C. elegans is providing new and unexpected insights into these questions, particularly questions relating to the hypertonic stress response (HTSR) pathway. One surprising characteristic of the HTSR pathway in C. elegans is that it is under strong negative regulation by proteins involved in protein homeostasis and the extracellular matrix (ECM). The role of the ECM in particular highlights the importance of studying the HTSR in the context of a live organism where native ECM-tissue associations are preserved. A second novel and recently discovered characteristic is that the HTSR is regulated at the post-transcriptional level. The goal of this review is to describe these discoveries, to provide context for their implications, and to raise outstanding questions to guide future research.

scholarly journals Does a Modified Math Emporium Work for All Students?

2020 ◽  
Vol 8 (3) ◽  
pp. 233
Author(s):  
Shannon Guerrero ◽  
Amanda Atherton ◽  
Amy Rushall ◽  
Robert Daugherty
Keyword(s):  
Student Performance ◽  
Developmental Mathematics ◽  
Future Research ◽  
Math Emporium ◽  
Large Numbers ◽  
Diverse Backgrounds ◽  
Race Ethnicity ◽  
The Impact ◽  
Emporium Model ◽  
International Status

Mathematics Emporia, or dedicated technology-supported learning environments designed to support large numbers of students in predominantly developmental mathematics courses, are a relatively recent phenomenon at community colleges and universities across the nation. While the size and number of these emporia has grown, empirical research into the impact of an emporium model on student learning and affect is only now emerging. This is especially true when looking at the impact of an emporium approach on students from diverse backgrounds. This study attempts to fill in the gaps in existing research related to how well emporium models address the needs of students based on gender, race/ethnicity, international status, and first- versus continuing-generation. Findings indicate that not all populations are served equally well by a modified mathematics emporium approach. The need for action to address inequities in student performance and implications for future research are discussed.

A Comprehensive Survey on Interoperability for IIoT: Taxonomy, Standards, and Future Directions

2023 ◽  
Vol 55 (1) ◽  
pp. 1-35
Author(s):  
Abhishek Hazra ◽  
Mainak Adhikari ◽  
Tarachand Amgoth ◽  
Satish Narayana Srirama
Keyword(s):  
Industrial Revolution ◽  
Industrial Applications ◽  
Future Research ◽  
The Internet ◽  
Large Numbers ◽  
Industrial Iot ◽  
Recent Developments ◽  
Comprehensive Survey ◽  
Real Time Information ◽  
The Internet Of Things

In the era of Industry 4.0, the Internet-of-Things (IoT) performs the driving position analogous to the initial industrial metamorphosis. IoT affords the potential to couple machine-to-machine intercommunication and real-time information-gathering within the industry domain. Hence, the enactment of IoT in the industry magnifies effective optimization, authority, and data-driven judgment. However, this field undergoes several interoperable issues, including large numbers of heterogeneous IoT gadgets, tools, software, sensing, and processing components, joining through the Internet, despite the deficiency of communication protocols and standards. Recently, various interoperable protocols, platforms, standards, and technologies are enhanced and altered according to the specifications of the applicability in industrial applications. However, there are no recent survey papers that primarily examine various interoperability issues that Industrial IoT (IIoT) faces. In this review, we investigate the conventional and recent developments of relevant state-of-the-art IIoT technologies, frameworks, and solutions for facilitating interoperability between different IIoT components. We also discuss several interoperable IIoT standards, protocols, and models for digitizing the industrial revolution. Finally, we conclude this survey with an inherent discussion of open challenges and directions for future research.

Data Confidentiality on the Semantic Web

2008 ◽  
pp. 3309-3320
Author(s):  
Csilla Farkas
Keyword(s):  
Semantic Web ◽  
Formal Semantics ◽  
Future Research ◽  
Semantic Web Technologies ◽  
Inference Problem ◽  
Web Technologies ◽  
Ontology Language ◽  
Future Research Directions ◽  
Description Framework ◽  
Resource Description

This chapter investigates the threat of unwanted Semantic Web inferences. We survey the current efforts to detect and remove unwanted inferences, identify research gaps, and recommend future research directions. We begin with a brief overview of Semantic Web technologies and reasoning methods, followed by a description of the inference problem in traditional databases. In the context of the Semantic Web, we study two types of inferences: (1) entailments defined by the formal semantics of the Resource Description Framework (RDF) and the RDF Schema (RDFS) and (2) inferences supported by semantic languages like the Web Ontology Language (OWL). We compare the Semantic Web inferences to the inferences studied in traditional databases. We show that the inference problem exists on the Semantic Web and that existing security methods do not fully prevent indirect data disclosure via inference channels.

LARGE-SCALE INTERACTION STRATEGIES FOR ASYNCHRONOUS ONLINE DISCUSSION

2011 ◽  
pp. 70-86
Author(s):  
Paul Giguere ◽  
Scott W. Formica ◽  
Wayne M. Harding ◽  
Michele R. Cummins
Keyword(s):  
Instructional Design ◽  
Learning Environments ◽  
Large Scale ◽  
Online Discussion ◽  
Learning Objectives ◽  
Future Research ◽  
Design Issues ◽  
Scale Interaction ◽  
Large Numbers ◽  
Online Instructional Design

Designing online trainings or courses for large numbers of participants can prove to be challenging for instructors and facilitators. Online learning environments need to be structured in a way that preserves actual or perceived levels of interaction, participant perceptions of value and utility, and achievement of the learning objectives. This chapter describes five Large-Scale Interaction Strategies that offer guidance for addressing some of these online instructional design issues. Evaluation data are presented in support of two of the strategies, and recommendations are provided about how future research in this area might be conducted.

Zygnematophyceae: from living algae collections to the establishment of future models

2020 ◽  
Vol 71 (11) ◽  
pp. 3296-3304
Author(s):  
Hong Zhou ◽  
Klaus von Schwartzenberg
Keyword(s):  
Model Organism ◽  
Past Research ◽  
Model Organisms ◽  
Current Status ◽  
Future Research ◽  
Suitable Model ◽  
Research Perspectives ◽  
Robust Model ◽  
Physiological Adaptations ◽  
Long Time

Abstract The class of conjugating green algae, Zygnematophyceae (Conjugatophyceae), is extremely rich in species and has attracted the interest of phycologists for a long time. It is now widely accepted that this class of charophyte algae holds a key position in the phylogenetic tree of streptophytes, where they represent the closest relatives to all land plants (embryophytes). It is increasingly evident that robust model plants that can be easily cultivated and genetically transformed are necessary to better understand the process of terrestrialization and the related molecular, cellular, and physiological adaptations. Living algae collections play an important role, not only for phylogenomic-based taxonomy but also for screening for suitable model organisms. For this review, we screened six major public algae collections for Zygnematophyceae strains and established a cumulative list comprising 738 different taxa (including species, subspecies, varieties, and forms). From the described biodiversity with 8883 registered taxa (AlgaeBase) the cultured Zygnematophyceae taxa worldwide cover only ~8.3%. We review the past research on this clade of algae and discuss it from the perspective of establishing a model organism. We present data on the life cycle of the genera Micrasterias and Spirogyra, representing the orders Desmidiales and Zygnematales, and outline the current status of genetic transformation of Zygnematophyceae algae and future research perspectives.

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