scholarly journals The CombineArchive Toolkit - facilitating the transfer of research results

2014 ◽  
Author(s):  
Martin Scharm ◽  
Florian Wendland ◽  
Martin Peters ◽  
Markus Wolfien ◽  
Tom Theile ◽  
...  
Keyword(s):  
Computational Biology ◽  
In Silico ◽  
Reproducible Research ◽  
Research Results ◽  
Manual Handling

Sharing in silico experiments is essential for the advance of research in computational biology. Consequently, the COMBINE archive was designed as a digital container format. It eases the management of numerous files, fosters collaboration, and ultimately enables the exchange of reproducible research results. However, manual handling of COMBINE archives is tedious and error prone. We therefore developed the CombineArchive Toolkit. It supports scientists in promoting and publishing their work by means of creating, exploring, modifying, and sharing archives.

scholarly journals The CombineArchive Toolkit - facilitating the transfer of research results

2014 ◽  
Author(s):  
Martin Scharm ◽  
Florian Wendland ◽  
Martin Peters ◽  
Markus Wolfien ◽  
Tom Theile ◽  
...  
Keyword(s):  
Computational Biology ◽  
In Silico ◽  
Reproducible Research ◽  
Research Results ◽  
Manual Handling

Sharing in silico experiments is essential for the advance of research in computational biology. Consequently, the COMBINE archive was designed as a digital container format. It eases the management of numerous files, fosters collaboration, and ultimately enables the exchange of reproducible research results. However, manual handling of COMBINE archives is tedious and error prone. We therefore developed the CombineArchive Toolkit. It supports scientists in promoting and publishing their work by means of creating, exploring, modifying, and sharing archives.

scholarly journals The CombineArchiveWeb application – A web based tool to handle files associated with modelling results

2014 ◽  
Author(s):  
Martin Scharm ◽  
Florian Wendland ◽  
Martin Peters ◽  
Markus Wolfien ◽  
Tom Theile ◽  
...  
Keyword(s):  
Computational Biology ◽  
In Silico ◽  
Simulation Studies ◽  
Meta Data ◽  
Web Based ◽  
Manual Handling ◽  
The Web

Sharing in silico experiments is essential for the advance of research in computational biology. Consequently, the COMBINE archive was designed as a digital container format. It eases the management of files related to a modelling result, fosters collaboration, and ultimately enables the exchange of reproducible simulation studies. However, manual handling of COMBINE archives is tedious and error prone. We therefore developed the CombineArchiveWeb application to support scientists in promoting and publishing their research by means of creating, exploring, modifying, and sharing archives. All files are equipped with meta data and can be distributed over the Web through shareable workspaces.

scholarly journals Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit

2015 ◽  
Author(s):  
Martin Scharm ◽  
Dagmar Waltemath
Keyword(s):  
Computational Biology ◽  
Simulation Study ◽  
Reproducible Research ◽  
Virtual Experiment ◽  
Graph Database ◽  
Simulation Studies ◽  
Valuable Resource ◽  
Open Model ◽  
Research Results ◽  
Biomodels Database

The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchiveToolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.

scholarly journals The CombineArchiveWeb application – A web based tool to handle files associated with modelling results

2014 ◽  
Author(s):  
Martin Scharm ◽  
Florian Wendland ◽  
Martin Peters ◽  
Markus Wolfien ◽  
Tom Theile ◽  
...  
Keyword(s):  
Computational Biology ◽  
In Silico ◽  
Simulation Studies ◽  
Meta Data ◽  
Web Based ◽  
Manual Handling ◽  
The Web

Sharing in silico experiments is essential for the advance of research in computational biology. Consequently, the COMBINE archive was designed as a digital container format. It eases the management of files related to a modelling result, fosters collaboration, and ultimately enables the exchange of reproducible simulation studies. However, manual handling of COMBINE archives is tedious and error prone. We therefore developed the CombineArchiveWeb application to support scientists in promoting and publishing their research by means of creating, exploring, modifying, and sharing archives. All files are equipped with meta data and can be distributed over the Web through shareable workspaces.

scholarly journals Extracting reproducible simulation studies from model repositories using the CombineArchive Toolkit

2015 ◽  
Author(s):  
Martin Scharm ◽  
Dagmar Waltemath
Keyword(s):  
Computational Biology ◽  
Simulation Study ◽  
Reproducible Research ◽  
Virtual Experiment ◽  
Graph Database ◽  
Simulation Studies ◽  
Valuable Resource ◽  
Open Model ◽  
Research Results ◽  
Biomodels Database

The COMBINE archive is a digital container format for files related to a virtual experiment in computational biology. It eases the management of numerous files related to a simulation study, fosters collaboration, and ultimately enables the exchange of reproducible research results. The CombineArchive Toolkit is a software for creating, exploring, modifying, and sharing COMBINE archives. Open model repositories such as BioModels Database are a valuable resource of models and associated simulation descriptions. However, so far no tool exists to export COMBINE archives for a given simulation study from such databases. Here we demonstrate how the CombineArchiveToolkit can be used to extract reproducible simulation studies from model repositories. We use the example of Masymos, a graph database with a sophisticated link concept to connect model-related files on the storage layer.

scholarly journals IN SILICO MODELING OF THE MOLECULAR STRUCTURE OF microRNAs MARKERS FOR LIVER FIBROSIS IN HEPATITIS C

2019 ◽  
Vol 48 (3) ◽  
pp. 135-147
Author(s):  
Gabriela Correia Matos de Oliveira ◽  
Raymundo Paraná ◽  
Luís Jesuino De Oliveira Andrade
Keyword(s):  
Molecular Structure ◽  
Hepatitis C ◽  
Nucleotide Sequence ◽  
Computational Biology ◽  
Hepatic Fibrosis ◽  
In Silico ◽  
Computational Simulation ◽  
Micro Rna ◽  
Nucleotide Sequence Alignment ◽  
In Silico Modeling

Molecular biology looks for evidence that microRNA (miRNAs) plays a relevant function both in the beginning and advanced stages of hepatic fibrosis (HF), and has been proposed as an additional biomarker for HF forecasting in carriers of hepatitis C virus (HCV) infection. The purpose of this study was to develop an in silico modeling of the two-dimensional (2D) molecular structure of miRNA markers for HF in carriers of HCV. A search was initially performed for the nucleotide sequence of 6 miRNAs defined as biomarkers for HF, performinga computational simulation of the molecular structure of the following miRNAs: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The nucleotide sequences were chosen in the GenBank of the American National Institutes of Health genetic sequence database. The nucleotide sequence alignment was carried out with a text-based format (FASTA) tool. In the molecular modeling, the structures were built with the RNAstructure, a completely automated miRNAs structure modelling server, available through Web Servers for RNA Secondary Structure Prediction. This study presented the nucleotide sequence and the computational simulation of molecular structures for the following miRNA: miRNA-182, miRNA-183, miRNA-1260b, miRNA-122-3p, miRNA-378i, and miRNA-214-5p. The molecular structure of miRNAs markers for HF in HCV carriers, through computational biology, is essential for designing more efficient optional tools for accurate treatment.  KEY WORDS: micro-RNA; Hepatitis C; Hepatic Fibrosis; Computational Biology.

scholarly journals A call for virtual experiments: accelerating the scientific process

2014 ◽  
Author(s):  
Jonathan Cooper ◽  
Jon Olav Vik ◽  
Dagmar Waltemath
Keyword(s):  
Computational Biology ◽  
Computational Models ◽  
Thought Experiment ◽  
Reproducible Research ◽  
Biological Knowledge ◽  
Initial State ◽  
Simulation Experiments ◽  
Specific Stimulus ◽  
Virtual Experiments ◽  
Experimental Protocols

Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. In the exploration of a novel system, children and researchers alike will mess about with things just to see what happens. More formalized experimental protocols ensure reproducible results and form a basis for comparing systems in terms of their response to a specific stimulus. Finally, experiments can be carefully designed to distinguish between competing causal hypotheses based on their different testable predictions about the outcome of the experimental manipulation. One would therefore expect experiments to be central in computational biology too. Indeed, a mathematical model embodies a thought experiment, a causal hypothesis, and its falsifiable predictions. It is easy to ask "what if" we were to change a parameter, an initial state, or the model structure. Papers in computational biology focus on describing and analyzing the effects of such changes, and on confronting models with experimental data. This confrontation often generates new hypotheses, and many if not most new models arise by modification of existing ones. However, most virtual experiments are not built to be reproducible, and thus die with the paper they are published in. This inhibits the critical scrutiny of models, as models are seldom subjected to the same simulation experiments as their predecessors, or revisited later in the light of new data. Perhaps worse, the status quo fails to take full advantage of experiments as a common language between modellers and experimentalists. Despite the growing availability of data and model repositories, there has been only a slow uptake of emerging tools and standards for documenting and sharing the protocols for simulation experiments and their results. We argue that promoting the reuse of virtual experiments would vastly improve the usefulness and relevance of computational models, including in biomedical endeavours such as the Virtual Physiological Human and the Human Brain Project. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the application of computational biology models. Next, we discuss potential approaches for implementing virtual experiments, arguing that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. We follow with some consideration of open questions and challenges that remain before the use of virtual experiments can become widespread. Lastly, we outline a vision for how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, akin to the strategy used in software development.

An Epistemological Analysis of QSPR/QSAR Models

2011 ◽  
pp. 318-332
Author(s):  
Jordi Vallverdú
Keyword(s):  
Drug Design ◽  
Computer Science ◽  
In Silico ◽  
Research Field ◽  
Research Results ◽  
Qsar Models ◽  
Epistemological Analysis ◽  
Scientific Value ◽  
The Way

Computer sciences have deeply changed the way by which we make science or produce knowledge. With the era of computers and the development of computer science, quantum chemists were among the first scientists to explore the potentialities of the new tool, and even to collaborate in its development. In this way, they also became participants in what many dubbed as the Second Instrumental Revolution in chemistry. Deeply involved into this research field, QSAR methods are powerful tools to create knowledge on toxicology and drug design, among others. There are several epistemological questions to be analyzed in order to understand the truth and scientific value of their research results (from in silico to wet laboratories and vice versa).

BEAMLAB AND REPRODUCIBLE RESEARCH

2004 ◽  
Vol 02 (04) ◽  
pp. 391-414 ◽  
Author(s):  
DAVID L. DONOHO ◽  
XIAOMING HUO
Keyword(s):  
Conference Proceedings ◽  
Software Package ◽  
Source Code ◽  
Geometric Analysis ◽  
Reproducible Research ◽  
The Internet ◽  
Interested Reader ◽  
Research Results ◽  
Source Codes ◽  
Numerical Studies

In the first 'Wavelets and Statistics' conference proceedings 1, our group published 'Wavelab and Reproducible Research', in which we advocated using the internet for publication of software and data so that research results could be duplicated by others. Much has happened in the last decade that bears on the notion of reproducibility, and we will review our experience. We will also describe a new software package BEAMLAB containing routines for multiscale geometric analysis, and describe some of its capabilities. BEAMLAB makes available, in one package, all the code to reproduce all the figures in our recently published articles on beamlets, curvelets and ridgelets. The interested reader can inspect the source code to see what algorithms were used, and how parameters were set to produce the figures, and will then be able to modify the source codes to produce variations of our results. Some new examples of numerical studies based on BEAMLAB are provided here.

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