FOntCell: Fusion of Ontologies of Cells

AbstractHigh-throughput cell-data technologies such as single-cell RNA-Seq create a demand for algorithms for automatic cell classification and characterization. There exist several classification ontologies of cells with complementary information. However, one needs to merge them in order to combine synergistically their information. The main difficulty in merging is to match the ontologies since they use different naming conventions. To overcome this obstacle we developed an algorithm that merges ontologies by integrating the name-matching search between class label names with the structure mapping between the ontology elements. To implement our algorithms, we developed FOntCell, a software module in Python for efficient automatic parallel-computed fusion of ontologies in the same or similar knowledge domains. It processes the ontology attributes to extract relations and class synonyms. FOntCell integrates the semantic, name with synonyms, mapping with a structure mapping based on graph convolution. Since the structure mapping assessment is time consuming process, we designed two methods to perform the graph convolution: vectorial structure matching and constraint-based structure matching. To perform the vectorial structure matching we designed a general method to calculate the similarities between vectors of different lengths for different metrics. Additionally, we adapted the slower Blondel method to work for structure matching. These functionalities of FOntCell allow the unification of dispersed knowledge in one domain into a unique ontology. FOntCell produces the results of the merged ontology in OBO format that can be iteratively reused by FOntCell to adapt continuously the ontologies with the new data, such of the Human Cell Atlas, endlessly produced by data-driven classification methods. To navigate easily across the fused ontologies, it generates HTML files with tabulated and graphic summaries, and an interactive circular Directed Acyclic Graphs of the merged results. We used FOntCell to fuse CELDA, LifeMap and LungMAP Human Anatomy cell ontologies to produce comprehensive cell ontology.Author SummaryThere is a strong belief in the research community that there exist more cell types than the described in the literature, therefore new technologies were developed to produce a high volume of data to discover new cells. One issue that arises once the cells are discovered is how to classify them. One way to perform such classification is to use already existing cell classifications from different ontology sources but it is difficult to merge them. An ontology has semantic information providing the meaning of each term and structural information providing the relationship between terms as a graph. We developed a new Python module, FOntCell that merges efficiently cell ontologies and integrates semantic and structure information with our own graph convolution technique. Since the structure mapping assessment is time-consuming process we designed two methods to optimize the graph convolution: vectorial and constraint-based structure matching. To perform the vectorial structure matching we designed a method that calculates the similarities between vectors describing the graphs of different sizes. The functionalities of FOntCell allow the unification of dispersed knowledge into a unique ontology, to adapt continuously from new data, and to navigate across the fused ontologies by a graphic use interface.

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FOntCell: Fusion of Ontologies of Cells

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.562908 ◽

2021 ◽

Vol 9 ◽

Author(s):

Javier Cabau-Laporta ◽

Alex M. Ascensión ◽

Mikel Arrospide-Elgarresta ◽

Daniela Gerovska ◽

Marcos J. Araúzo-Bravo

Keyword(s):

Geometric Mean ◽

Directed Acyclic Graphs ◽

Human Anatomy ◽

Ontology Alignment ◽

Structure Mapping ◽

Software Module ◽

Cell Classification ◽

Knowledge Domains ◽

Cell Ontology ◽

Vectorial Structure

High-throughput cell-data technologies such as single-cell RNA-seq create a demand for algorithms for automatic cell classification and characterization. There exist several cell classification ontologies with complementary information. However, one needs to merge them to synergistically combine their information. The main difficulty in merging is to match the ontologies since they use different naming conventions. Therefore, we developed an algorithm that merges ontologies by integrating the name matching between class label names with the structure mapping between the ontology elements based on graph convolution. Since the structure mapping is a time consuming process, we designed two methods to perform the graph convolution: vectorial structure matching and constraint-based structure matching. To perform the vectorial structure matching, we designed a general method to calculate the similarities between vectors of different lengths for different metrics. Additionally, we adapted the slower Blondel method to work for structure matching. We implemented our algorithms into FOntCell, a software module in Python for efficient automatic parallel-computed merging/fusion of ontologies in the same or similar knowledge domains. FOntCell can unify dispersed knowledge from one domain into a unique ontology in OWL format and iteratively reuse it to continuously adapt ontologies with new data endlessly produced by data-driven classification methods, such as of the Human Cell Atlas. To navigate easily across the merged ontologies, it generates HTML files with tabulated and graphic summaries, and interactive circular Directed Acyclic Graphs. We used FOntCell to merge the CELDA, LifeMap and LungMAP Human Anatomy cell ontologies into a comprehensive cell ontology. We compared FOntCell with tools used for the alignment of mouse and human anatomy ontologies task proposed by the Ontology Alignment Evaluation Initiative (OAEI) and found that the Fβ alignment accuracies of FOntCell are above the geometric mean of the other tools; more importantly, it outperforms significantly the best OAEI tools in cell ontology alignment in terms of Fβ alignment accuracies.

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TomoSAR Mapping of 3D Forest Structure: Contributions of L-Band Configurations

Remote Sensing ◽

10.3390/rs13122255 ◽

2021 ◽

Vol 13 (12) ◽

pp. 2255

Author(s):

Matteo Pardini ◽

Victor Cazcarra-Bes ◽

Konstantinos Papathanassiou

Keyword(s):

Information Content ◽

Forest Structure ◽

Structural Information ◽

3D Structure ◽

Physical Structure ◽

Structure Mapping ◽

Structure Information ◽

Forest Sites ◽

L Band ◽

Structure Indices

Synthetic Aperture Radar (SAR) measurements are unique for mapping forest 3D structure and its changes in time. Tomographic SAR (TomoSAR) configurations exploit this potential by reconstructing the 3D radar reflectivity. The frequency of the SAR measurements is one of the main parameters determining the information content of the reconstructed reflectivity in terms of penetration and sensitivity to the individual vegetation elements. This paper attempts to review and characterize the structural information content of L-band TomoSAR reflectivity reconstructions, and their potential to forest structure mapping. First, the challenges in the accurate TomoSAR reflectivity reconstruction of volume scatterers (which are expected to dominate at L-band) and to extract physical structure information from the reconstructed reflectivity is addressed. Then, the L-band penetration capability is directly evaluated by means of the estimation performance of the sub-canopy ground topography. The information content of the reconstructed reflectivity is then evaluated in terms of complementary structure indices. Finally, the dependency of the TomoSAR reconstruction and of its structural information to both the TomoSAR acquisition geometry and the temporal change of the reflectivity that may occur in the time between the TomoSAR measurements in repeat-pass or bistatic configurations is evaluated. The analysis is supported by experimental results obtained by processing airborne acquisitions performed over temperate forest sites close to the city of Traunstein in the south of Germany.

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Rapid determination of fractal structure of bacterial assemblages in wastewater treatment: implications to process optimisation

Water Science & Technology ◽

10.2166/wst.1998.0092 ◽

1998 ◽

Vol 38 (2) ◽

pp. 9-15 ◽

Cited By ~ 3

Author(s):

J. Guan ◽

T. D. Waite ◽

R. Amal ◽

H. Bustamante ◽

R. Wukasch

Keyword(s):

Wastewater Treatment ◽

Fractal Structure ◽

Structural Information ◽

Rapid Determination ◽

Fractal Dimensions ◽

Structure Information ◽

Treatment Processes ◽

On Line ◽

Bacterial Aggregates

A rapid method of determining the structure of aggregated particles using small angle laser light scattering is applied here to assemblages of bacteria from wastewater treatment systems. The structure information so obtained is suggestive of fractal behaviour as found by other methods. Strong dependencies are shown to exist between the fractal structure of the bacterial aggregates and the behaviour of the biosolids in zone settling and dewatering by both pressure filtration and centrifugation methods. More rapid settling and significantly higher solids contents are achievable for “looser” flocs characterised by lower fractal dimensions. The rapidity of determination of structural information and the strong dependencies of the effectiveness of a number of wastewater treatment processes on aggregate structure suggests that this method may be particularly useful as an on-line control tool.

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Overview of Forming and Formability Issues for High Volume Aluminium Car Body Panels

Materials Science Forum ◽

10.4028/www.scientific.net/msf.519-521.795 ◽

2006 ◽

Vol 519-521 ◽

pp. 795-802 ◽

Cited By ~ 7

Author(s):

Dominique Daniel ◽

Gilles Guiglionda ◽

Pierre Litalien ◽

Ravi Shahani

Keyword(s):

New Technologies ◽

High Volume ◽

Production Lines ◽

Particle Generation ◽

Car Body ◽

Conventional Technology ◽

Sheet Products ◽

Cost Efficient ◽

Aluminum Panels ◽

Fine Tune

Cost-efficient designs of aluminum autobody structures consist mainly of stampings using conventional technology. Progress in metallurgy and forming processes has enabled aluminum body panels to achieve significant market share, particularly for hoods. Fast bake hardening alloys with better hemming performance were developed for improved outer panel sheet products. Specific guidelines for handling and press working were established to form aluminum panels using similar schedules and production lines as steel parts. Stamping productivity was improved by optimization of the trimming process to reduce sliver/particle generation and resulting end-of-line manual rework. Both hemming formability and trimming quality not only depend on tooling setup but also on microstructural features, which govern intrinsic alloy ductility. Targets for the next high volume aluminum car body applications, such as roof panels and doors, require higher strength and/or better formability. The challenges of complex stampings can be met with optimized alloys and lubricants, with improved numerical simulation to fine-tune stamping process parameters, and with the introduction of new technologies. Warm forming was examined as a potential breakthrough technology for high volume stamping of complex geometries.

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NMR-Based Structural Characterization of a Two-Disulfide-Bonded Analogue of the FXIIIa Inhibitor Tridegin: New Insights into Structure–Activity Relationships

International Journal of Molecular Sciences ◽

10.3390/ijms22020880 ◽

2021 ◽

Vol 22 (2) ◽

pp. 880

Author(s):

Thomas Schmitz ◽

Ajay Abisheck Paul George ◽

Britta Nubbemeyer ◽

Charlotte A. Bäuml ◽

Torsten Steinmetzer ◽

...

Keyword(s):

Structural Information ◽

Coagulation Factor ◽

Md Simulations ◽

2D Nmr ◽

Label Free ◽

2D Nmr Spectroscopy ◽

Structure Information ◽

Structure Activity Relationships ◽

Structure Activity ◽

Blood Sucking

The saliva of blood-sucking leeches contains a plethora of anticoagulant substances. One of these compounds derived from Haementeria ghilianii, the 66mer three-disulfide-bonded peptide tridegin, specifically inhibits the blood coagulation factor FXIIIa. Tridegin represents a potential tool for antithrombotic and thrombolytic therapy. We recently synthesized two-disulfide-bonded tridegin variants, which retained their inhibitory potential. For further lead optimization, however, structure information is required. We thus analyzed the structure of a two-disulfide-bonded tridegin isomer by solution 2D NMR spectroscopy in a combinatory approach with subsequent MD simulations. The isomer was studied using two fragments, i.e., the disulfide-bonded N-terminal (Lys1–Cys37) and the flexible C-terminal part (Arg38–Glu66), which allowed for a simplified, label-free NMR-structure elucidation of the 66mer peptide. The structural information was subsequently used in molecular modeling and docking studies to provide insights into the structure–activity relationships. The present study will prospectively support the development of anticoagulant-therapy-relevant compounds targeting FXIIIa.

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Characterization of Tilt Boundaries by Ultra High Resolution Electron Microscopy

MRS Proceedings ◽

10.1557/proc-41-253 ◽

1984 ◽

Vol 41 ◽

Cited By ~ 2

Author(s):

W. Krakow ◽

J. T. Wetzel ◽

D. A. Smith ◽

G. Trafas

Keyword(s):

High Resolution ◽

Grain Boundary ◽

Structural Information ◽

Theoretical Work ◽

High Resolution Electron Microscopy ◽

Point Of View ◽

Experimental Point ◽

Structure Information ◽

Resolution Electron ◽

Tilt Boundaries

AbstractA high resolution electron microscope study of grain boundary structures in Au thin films has been undertaken from both a theoretical and experimental point of view. The criteria necessary to interpret images of tilt boundaries at the atomic level, which include electron optical and specimen effects, have been considered for both 200kV and the newer 400kV medium voltage microscopes. So far, the theoretical work has concentrated on two different [001] tilt bounda-ries where a resolution of 2.03Å is required to visualize bulk lattice structures on either side of the interface. Both a high angle boundary, (210) σ=5, and a low angle boundary, (910) σ=41, have been considered. Computational results using multislice dynamical diffraction and image simulations of relaxed bounda-ries viewed edge-on and with small amounts of beam and/or specimen inclina-tion have been obtained. It will be shown that some structural information concerning grain boundary dislocations can be observed at 200kV. However, many difficulties occur in the exact identification of the interface structure viewed experimentally for both [001] and [011] boundaries since the resolution required is near the performance limit of a 200kV microscope. The simulated results at 400kV indicate a considerable improvement will be realized in obtain-ing atomic structure information at the interface.

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Building data analytics skills for clinical drug development quality professionals - the Data Analytics University training program

10.21203/rs.3.rs-199575/v1 ◽

2021 ◽

Author(s):

Sharon Havenhad ◽

Björn Koneswarakantha ◽

Donato Rolo ◽

Pooja Mehta ◽

Rich Bowling ◽

...

Keyword(s):

Drug Development ◽

Training Program ◽

Data Analytics ◽

New Technologies ◽

High Volume ◽

Clinical Drug Development ◽

Data Driven Approach ◽

E Learning ◽

University Training ◽

Clinical Drug

Abstract Clinical drug development is a complex and extensive process that entails multiple stakeholders alongside patients, requires large capital expenditures and takes nearly a decade on average to complete. To ensure the correct development of this process, rigorous quality activities must be conducted to assess and guarantee the Good Clinical and Pharmacovigilance Practices (GxP) for study compliance. For about 25 years, most of these activities have been performed in the form of audits, which implies a high volume of manual work and resources in addition to being reactive by nature. Due to the limitations of this approach, together with intent to leverage new technologies in the data analytics field, a more holistic, proactive and data-driven approach needed to take place. For this to happen, quality assurance expertise needed to be complemented by the data literacy skillset. To achieve this, the Data Analytics University (DAU) was created. An in-house training program composed by two pathways that provided a framework for clinical quality staff to develop their data analytics capabilities. The first pathway covers the basics of statistics, probability and data-related terminology, while the second deepens further into the topics covered in the former followed by hands-on activities to put the knowledge to test. After successful completion of 15 DAU sessions, over 310 trained staff were able to apply their learning on data analytics and solve potential issues that might arise with a given dataset. In the near future, the DAU will be made available externally as an e-learning training program.

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Genomic Landscape of Cancer

10.1093/oso/9780190238667.003.0004 ◽

2017 ◽

Author(s):

Christopher J. Maher ◽

Elaine R. Mardis

Keyword(s):

Dna Sequencing ◽

Tumor Tissue ◽

New Technologies ◽

Cancer Genomics ◽

Protein Complexes ◽

High Volume ◽

Genetic Alterations ◽

Abnormal Growth ◽

Genomic Landscape ◽

The Cost

The study of cancer genomics has advanced rapidly during the last decade due to the development of next generation or massively parallel technology for DNA sequencing. The resulting knowledge is transforming the understanding of both inherited (germline) genetic susceptibility and the somatic changes in tumor tissue that drive abnormal growth and progression. The somatic alterations in tumor tissue vary depending on the type of cancer and its characteristic “genomic landscape.” New technologies have increased the speed and lowered the cost of DNA sequencing and have enabled high-volume characterization of RNA, DNA methylation, DNA-protein complexes, DNA conformation, and a host of other factors that, when altered, can contribute to the development and/or progression of the cancer. Technologic advances have greatly expanded research on somatic changes in tumor tissue, revealing both the singularity of individual cancer genomes and the commonality of genetic alterations that drive cancer in different tissues.

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Restructuring of the boreal forest and the forest sector in Newfoundland, Canada

The Forestry Chronicle ◽

10.5558/tfc85772-5 ◽

2009 ◽

Vol 85 (5) ◽

pp. 772-782 ◽

Cited By ~ 2

Author(s):

Brian McLaren ◽

Jason Pollard

Keyword(s):

New Technologies ◽

Labour Productivity ◽

High Volume ◽

Steady Increase ◽

Forest Sector ◽

Paper Mills ◽

Wood Extraction ◽

Forested Landscapes ◽

History Of ◽

Transportation Technologies

Newfoundland pulp logs were once considered an abundant resource available for export, but over the last part of the 20th century became a shrinking commodity, imported to the island to keep 3 paper mills supplied. What were the concurrent changes in the human and the forested landscapes? Faced with increasing resource and labour costs, forest operations became increasingly centralized and mechanized during the second half of the 20th century. Labour productivity increased and, until the mid-1970s, pulpwood processing also increased as a means for forest companies to remain competitive. By the mid-1970s, processed volumes began to fall, but the number of employees in the forest sector continued to decline, resulting in a steady increase in the volume of pulpwood required to support a forest sector job. Forests accessed by loggers were first concentrated around waterways and then became more dispersed across the landscape, as a result of changes in wood extraction and transportation technologies. Beginning in the 1950s and increasingly through the 1980s, pulpwood was cut from targeted, high-volume stands. Eventually 2 of the 3 paper mills was forced to close, in part because of higher costs associated with accessing pulpwood. Newfoundland’s history of forestry restructuring is similar to the experience elsewhere in Canada. We suggest that signals of overexploitation have been often overlooked by policy-makers and changes in the forest sector can be more easily viewed as a response to new technologies and global markets than policy-making. Key words: Canada, employment, history, landscape, logging, Newfoundland and Labrador, policy, restructuring, sustainability

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