scholarly journals Effect of Superpixel Aggregation on Explanations in LIME – A Case Study with Biological Data

2020 ◽  
pp. 147-158
Author(s):  
Ludwig Schallner ◽  
Johannes Rabold ◽  
Oliver Scholz ◽  
Ute Schmid
Keyword(s):  
Biological Data

GRASP with Path-Relinking for Data Clustering: A Case Study for Biological Data

2011 ◽  
pp. 410-420 ◽  
Author(s):  
Rafael M. D. Frinhani ◽  
Ricardo M. A. Silva ◽  
Geraldo R. Mateus ◽  
Paola Festa ◽  
Mauricio G. C. Resende
Keyword(s):  
Data Clustering ◽  
Biological Data ◽  
Path Relinking

scholarly journals Assessing marine biosecurity risks when data are limited: bioregion pathway and species-based exposure analyses

2014 ◽  
Vol 72 (3) ◽  
pp. 1078-1091 ◽  
Author(s):  
Fauziah Azmi ◽  
Carmen Primo ◽  
Chad L. Hewitt ◽  
Marnie L. Campbell
Keyword(s):  
Biological Data ◽  
Exposure Model ◽  
Northwest Pacific ◽  
Pathway Model ◽  
Risk Models ◽  
Data Intensive ◽  
Threat Categories ◽  
Watch List ◽  
Theoretical Risk

Abstract We evaluated two risk models (bioregion pathway and species-based exposure), with the aim to determine an effective strategy to implement marine biosecurity risk management in regions/countries where biological data are limited. We used the Port of Tanjung Priok, Jakarta Bay, Indonesia, as a case study to test both models. The bioregion pathway model illustrates that Tanjung Priok is highly connected to the East Asian Sea (∼91%), and the Northwest Pacific, Mediterranean, and Australia & New Zealand bioregions (“Very Low” risk), with other bioregions posing “Negligible” risk, highlighting the importance of understanding regional port linkages. The bioregion pathway model strength is grounded by using readily available shipping data; however, it does not classify species into threat categories but considers a larger number of species as an increasing threat. The species exposure model found that 51 species pose a theoretical risk (10 “Moderate”, 20 “High”, and 21 “Extreme” risks) to Tanjung Priok. These 51 species can be used as a “watch list” for this port. If biosecurity measures for this port were restricted to the outcomes of the bioregion pathway model only 4 of the 51 species highlighted by the species exposure model would have been captured. The species model was data intensive, requiring extensive species datasets and consequently may be unsuitable when data are limited.

scholarly journals Geospatial web services for limnological data: a case study of sensor observation service for ecological observations

2014 ◽  
Vol II-4 ◽  
pp. 9-14 ◽  
Author(s):  
C. Arias Muñoz ◽  
A. Oggioni ◽  
M. A. Brovelli
Keyword(s):  
Web Services ◽  
Spatial Data ◽  
Drainage Basin ◽  
Biological Species ◽  
Biological Data ◽  
Environmental Data ◽  
Ecological Data ◽  
Essential Components ◽  
Geospatial Web Services

The present work aims at designing and implementing a spatial data infrastructure for storing and sharing ecological data through geospatial web services. As case study, we concentrated on limnological data coming from the drainage basin of Lake Maggiore in the Northern of Italy. In order to establish the infrastructure, we started with two basic questions: (1) What type of data is the ecological dataset? (2) Which are the geospatial web services standards most suitable to store and share ecological data? In this paper we describe the possibilities for sharing ecological data using geospatial web services and the difficulties that can be encountered in this task. In order to test actual technological solutions, we use real data of a limnological published study.We concluded that limnological data can be considered observational data, composed by biological (species) data and environmental data, and it can be modeled using Observation and Measurement (O&M) specification. With the actual web service implementation the geospatial web services that could potentially be used to publish limnological data are Sensor Observation Services (SOS) and Web Feature Services (WFS). SOS holds the essential components to represent time series observations, while WFS is a simple model that requires profiling. Both, SOS and WFS are not perfectly suitable to publish biological data, so other alternatives must be considered, as linked data.

scholarly journals A Cross Disciplinary Framework for Cost-Benefit Optimization of Marine Litter Cleanup at Regional Scale

2021 ◽  
Vol 8 ◽  
Author(s):  
Asbjørn Christensen ◽  
Kostas Tsiaras ◽  
Jens Murawski ◽  
Yannis Hatzonikolakis ◽  
Jun She ◽  
...  
Keyword(s):  
Ecosystem Functioning ◽  
Government Regulation ◽  
Regional Scale ◽  
Cost Benefit ◽  
Real Data ◽  
Biological Data ◽  
Transport Modeling ◽  
Marine Litter ◽  
Bridge Building

Litter cleanup and disposal management in the marine environment are increasingly subject to public scrutiny, government regulation and stakeholder initiatives. In practice, ongoing efforts and new investment decisions, for example in new cleanup technologies, are constrained by financial and economic resources. Given budgetary restrictions, it is important to optimize decision-making using a scientific framework that takes into account the various effects of investments by combining multiple scientific perspectives and integrating these in a consistent and coherent way. Identifying optimal levels of marine litter cleanup is a challenge, because of its cross-disciplinary nature, involving physics, environmental engineering, science, and economics. In this paper, we propose a bridge-building, spatial cost-benefit optimization framework that allows prioritizing where to apply limited cleanup efforts within a regional spatial network of marine litter sources, using input from the maturing field of marine litter transport modeling. The framework also includes ecosystem functioning in relation to variable litter concentrations, as well as the potentially non-linear cost-efficiency of cleanup technologies. From these three components (transport modeling, ecosystem functioning, cleanup-effectiveness), along with litter source mapping, we outline the optimal cleanup solution at any given ecological target or economic constraint, as well as determine the cleanup feasibility. We illustrate our framework in a Baltic and Mediterranean Sea case study, using real data for litter transport and cleanup technology. Our study shows that including pollution Green's functions is essential to assess the feasibility of cleanup and determine optimal deployment of cleanup investments, where the presented framework combines physical, economical, technological and biological data consistently to compare and rank alternatives.

scholarly journals Reconstruction of biological networks based on life science data integration

2010 ◽  
Vol 7 (2) ◽  
Author(s):  
Benjamin Kormeier ◽  
Klaus Hippe ◽  
Patrizio Arrigo ◽  
Thoralf Töpel ◽  
Sebastian Janowski ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Data Integration ◽  
Biological Networks ◽  
Life Science ◽  
Biological Network ◽  
Network Models ◽  
Biological Data ◽  
Science Data ◽  
Biological Data Integration

SummaryFor the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

scholarly journals Using Data Warehouse Technology in Crop Plant Bioinformatics

2007 ◽  
Vol 4 (1) ◽  
pp. 145-159 ◽  
Author(s):  
Christian Kuenne ◽  
Ivo Grosse ◽  
Inge Matthies ◽  
Uwe Scholz ◽  
Tatjana Sretenovic-Rajicic ◽  
...  
Keyword(s):  
Data Warehouse ◽  
Case Studies ◽  
Biological Data ◽  
Current Case ◽  
Specific Data ◽  
Barley Cultivars ◽  
Solution Strategies ◽  
Using Data ◽  
Diversity Studies

Summary Plant-specific data is managed in heterogeneous formats and is dispersed geographically. Based on this data, efficient analyses require a materialised integration, often realised with data warehouse technology today. We describe the requirements, problems and solution strategies for domain-crossing integration as the fundament for analysing plant biological data based on three current case studies. First, we introduce a system for retrieval of markers and mapping positions based on clustering of ESTs. The second case study illustrates the steps for diversity studies after genotyping a collection of about 3,000 ryegrass accessions (Lolium spp.), whereas in the third example data of approximately 250 barley cultivars (Hordeum vulgare) were used for associating haplotype- and SNP-patterns with malting parameters. For all case studies, we integrate data from different domains - sequence and marker data as well as IPK Genebank data including passport and phenotypic information. Specific problems associated with plant biological data and possible solution strategies are shown.

scholarly journals Can Bibliographic Pointers for Known Biological Data Be Found Automatically? Protein Interactions as a Case Study

2001 ◽  
Vol 2 (4) ◽  
pp. 196-206 ◽  
Author(s):  
Christian Blaschke ◽  
Alfonso Valencia
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Biological Data ◽  
Positive Finding ◽  
Data Set ◽  
Large Scale Assessment ◽  
Low Coverage ◽  
Standard Protein

The Dictionary of Interacting Proteins(DIP) (Xenarioset al., 2000) is a large repository of protein interactions: its March 2000 release included 2379 protein pairs whose interactions have been detected by experimental methods. Even if many of these correspond to poorly characterized proteins, the result of massive yeast two-hybrid screenings, as many as 851 correspond to interactions detected using direct biochemical methods.We used information retrieval technology to search automatically for sentences in Medline abstracts that support these 851 DIP interactions. Surprisingly, we found correspondence between DIP protein pairs and Medline sentences describing their interactions in only 30% of the cases. This low coverage has interesting consequences regarding the quality of annotations (references) introduced in the database and the limitations of the application of information extraction (IE) technology to Molecular Biology. It is clear that the limitation of analyzing abstracts rather than full papers and the lack of standard protein names are difficulties of considerably more importance than the limitations of the IE methodology employed. A positive finding is the capacity of the IE system to identify new relations between proteins, even in a set of proteins previously characterized by human experts. These identifications are made with a considerable degree of precision.This is, to our knowledge, the first large scale assessment of IE capacity to detect previously known interactions: we thus propose the use of the DIP data set as a biological reference to benchmark IE systems.

scholarly journals A case study of high-throughput biological data processing on parallel platforms

2004 ◽  
Vol 20 (12) ◽  
pp. 1940-1947 ◽  
Author(s):  
D. Pekurovsky ◽  
I. N. Shindyalov ◽  
P. E. Bourne
Keyword(s):  
Data Processing ◽  
High Throughput ◽  
Biological Data

scholarly journals Bioinformatics in Sudan: Status and challenges case study: The National University-Sudan

2021 ◽  
Vol 17 (10) ◽  
pp. e1009462
Author(s):  
Sofia B. Mohamed ◽  
Sumaya Kambal ◽  
Sabah A. E. Ibrahim ◽  
Esra Abdalwhab ◽  
Abdalla Munir ◽  
...  
Keyword(s):  
Research Funding ◽  
Statistical Tests ◽  
Research Community ◽  
Status Quo ◽  
Biological Data ◽  
Computational Tools ◽  
National University ◽  
Biomedical Research Institute ◽  
And Training

The ever increasing applications of bioinformatics in providing effective interpretation of large and complex biological data require expertise in the use of sophisticated computational tools and advanced statistical tests, skills that are mostly lacking in the Sudanese research community. This can be attributed to paucity in the development and promotion of bioinformatics, lack of senior bioinformaticians, and the general status quo of inadequate research funding in Sudan. In this paper, we describe the challenges that have encountered the development of bioinformatics as a discipline in Sudan. Additionally, we highlight on specific actions that may help develop and promote its education and training. The paper takes the National University Biomedical Research Institute (NUBRI) as an example of an institute that has tackled many of these challenges and strives to drive powerful efforts in the development of bioinformatics in the country.

scholarly journals Fuzzy association rules for biological data analysis: A case study on yeast

2008 ◽  
Vol 9 (1) ◽  
Author(s):  
Francisco J Lopez ◽  
Armando Blanco ◽  
Fernando Garcia ◽  
Carlos Cano ◽  
Antonio Marin
Keyword(s):  
Data Analysis ◽  
Association Rules ◽  
Biological Data ◽  
Fuzzy Association Rules ◽  
Biological Data Analysis
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