Encyclopedia of tools for the analysis of miRNA isoforms

2020 ◽  
Author(s):  
Georges Pierre Schmartz ◽  
Fabian Kern ◽  
Tobias Fehlmann ◽  
Viktoria Wagner ◽  
Bastian Fromm ◽  
...  
Keyword(s):  
Time Range ◽  
Data Sets ◽  
Sequencing Data ◽  
Comprehensive Overview ◽  
Computational Tools ◽  
Web Based ◽  
Analysis Tools ◽  
Research Task ◽  
Publication Time ◽  
Selection Of

Abstract RNA sequencing data sets rapidly increase in quantity. For microRNAs (miRNAs), frequently dozens to hundreds of billion reads are generated per study. The quantification of annotated miRNAs and the prediction of new miRNAs are leading computational tasks. Now, the increased depth of coverage allows to gain deeper insights into the variability of miRNAs. The analysis of isoforms of miRNAs (isomiRs) is a trending topic, and a range of computational tools for the analysis of isomiRs has been developed. We provide an overview on 27 available computational solutions for the analysis of isomiRs. These include both stand-alone programs (17 tools) and web-based solutions (10 tools) and span a publication time range from 2010 to 2020. Seven of the tools were published in 2019 and 2020, confirming the rising importance of the topic. While most of the analyzed tools work for a broad range of organisms or are completely independent of a reference organism, several tools have been tailored for the analysis of human miRNA data or for plants. While 14 of the tools are general analysis tools of miRNAs, and isomiR analysis is one of their features, the remaining 13 tools have specifically been developed for isomiR analysis. A direct comparison on 20 deep sequencing data sets for selected tools provides insights into the heterogeneity of results. With our work, we provide users a comprehensive overview on the landscape of isomiR analysis tools and in that support the selection of the most appropriate tool for their respective research task.

scholarly journals SOS: online probability estimation and generation of T-and B-cell receptors

2020 ◽  
Vol 36 (16) ◽  
pp. 4510-4512
Author(s):  
Giulio Isacchini ◽  
Carlos Olivares ◽  
Armita Nourmohammad ◽  
Aleksandra M Walczak ◽  
Thierry Mora
Keyword(s):  
B Cell ◽  
High Throughput Sequencing ◽  
B Cell Receptors ◽  
Sequencing Data ◽  
Vdj Recombination ◽  
Web Based ◽  
Cell Receptors ◽  
High Throughput Sequencing Data ◽  
Selection Probabilities ◽  
Selection Of

Abstract Summary Recent advances in modelling VDJ recombination and subsequent selection of T- and B-cell receptors provide useful tools to analyse and compare immune repertoires across time, individuals and tissues. A suite of tools—IGoR, OLGA and SONIA—have been publicly released to the community that allow for the inference of generative and selection models from high-throughput sequencing data. However, using these tools requires some scripting or command-line skills and familiarity with complex datasets. As a result, the application of the above models has not been available to a broad audience. In this application note, we fill this gap by presenting Simple OLGA & SONIA (SOS), a web-based interface where users with no coding skills can compute the generation and post-selection probabilities of their sequences, as well as generate batches of synthetic sequences. The application also functions on mobile phones. Availability and implementation SOS is freely available to use at sites.google.com/view/statbiophysens/sos with source code at github.com/statbiophys/sos.

scholarly journals MetroNome — a visual data exploration platform for integrating human genotypic and phenotypic data across diseases

2019 ◽  
Author(s):  
Christian Stolte ◽  
Kevin Shi ◽  
Nina Lapchyk ◽  
Nathaniel Novod ◽  
Avinash Abhyankar ◽  
...  
Keyword(s):  
Interactive Visualization ◽  
Data Exploration ◽  
Data Sets ◽  
Visual Data ◽  
Phenotypic Data ◽  
Web Based ◽  
Multimodal Data ◽  
Analysis Tools ◽  
New Ideas ◽  
Visual Data Exploration

AbstractMetroNome is a web-based visual data exploration platform which integrates de-identified genomic, transcriptomic, and phenotypic data sets. Users can define and compare cohorts constructed from multimodal data and share the data and analyses with outside tools. MetroNome’s interactive visualization and analysis tools allow researchers to quickly form and explore novel hypotheses. The deidentified data is linked back to the source biosample inventories in multiple biobanks, enabling researchers to further investigate new ideas using the most relevant samples.

Selection of one-dimensional sedimentation: models for on-line use

1995 ◽  
Vol 31 (2) ◽  
pp. 193-204 ◽  
Author(s):  
Koen Grijspeerdt ◽  
Peter Vanrolleghem ◽  
Willy Verstraete
Keyword(s):  
Steady State ◽  
Selection Criteria ◽  
Data Sets ◽  
Concentration Profiles ◽  
A Posteriori ◽  
One Dimensional ◽  
On Line ◽  
Dynamic Concentration ◽  
Selection Of ◽  
Modelling Task

A comparative study of several recently proposed one-dimensional sedimentation models has been made. This has been achieved by fitting these models to steady-state and dynamic concentration profiles obtained in a down-scaled secondary decanter. The models were evaluated with several a posteriori model selection criteria. Since the purpose of the modelling task is to do on-line simulations, the calculation time was used as one of the selection criteria. Finally, the practical identifiability of the models for the available data sets was also investigated. It could be concluded that the model of Takács et al. (1991) gave the most reliable results.

Web-based Tools for Drug Repurposing: Successful Examples of Collaborative Research

2020 ◽  
Vol 28 (1) ◽  
pp. 181-195
Author(s):  
Quentin Vanhaelen
Keyword(s):  
User Interfaces ◽  
Collaborative Research ◽  
Meta Analysis ◽  
A Priori ◽  
Drug Repurposing ◽  
Data Access ◽  
Estimation Methods ◽  
Large Set ◽  
Computational Tools ◽  
Web Based

: Computational approaches have been proven to be complementary tools of interest in identifying potential candidates for drug repurposing. However, although the methods developed so far offer interesting opportunities and could contribute to solving issues faced by the pharmaceutical sector, they also come with their constraints. Indeed, specific challenges ranging from data access, standardization and integration to the implementation of reliable and coherent validation methods must be addressed to allow systematic use at a larger scale. In this mini-review, we cover computational tools recently developed for addressing some of these challenges. This includes specific databases providing accessibility to a large set of curated data with standardized annotations, web-based tools integrating flexible user interfaces to perform fast computational repurposing experiments and standardized datasets specifically annotated and balanced for validating new computational drug repurposing methods. Interestingly, these new databases combined with the increasing number of information about the outcomes of drug repurposing studies can be used to perform a meta-analysis to identify key properties associated with successful drug repurposing cases. This information could further be used to design estimation methods to compute a priori assessment of the repurposing possibilities.

Real-time Approximation of Photometric Polygonal Lights

2020 ◽  
Vol 3 (1) ◽  
pp. 1-18
Author(s):  
Christian Luksch ◽  
Lukas Prost ◽  
Michael Wimmer
Keyword(s):  
Real Time ◽  
Specular Reflection ◽  
Near Field ◽  
Measurement Data ◽  
Data Sets ◽  
Photometric Measurement ◽  
Integration Technique ◽  
Time Approximation ◽  
Light Emitter ◽  
Selection Of

We present a real-time rendering technique for photometric polygonal lights. Our method uses a numerical integration technique based on a triangulation to calculate noise-free diffuse shading. We include a dynamic point in the triangulation that provides a continuous near-field illumination resembling the shape of the light emitter and its characteristics. We evaluate the accuracy of our approach with a diverse selection of photometric measurement data sets in a comprehensive benchmark framework. Furthermore, we provide an extension for specular reflection on surfaces with arbitrary roughness that facilitates the use of existing real-time shading techniques. Our technique is easy to integrate into real-time rendering systems and extends the range of possible applications with photometric area lights.

scholarly journals What Do Meditators Do When They Meditate? Proposing a Novel Basis for Future Meditation Research

Mindfulness ◽  
2021 ◽  
Author(s):  
Karin Matko ◽  
Ulrich Ott ◽  
Peter Sedlmeier
Keyword(s):  
Qualitative Study ◽  
Quantitative Study ◽  
Literature Search ◽  
Comprehensive Overview ◽  
Contemplative Practices ◽  
Comprehensive List ◽  
Scientific Investigations ◽  
Wide Range ◽  
Vast Range ◽  
Selection Of

Abstract Objectives Meditation is an umbrella term for a vast range of contemplative practices. Former proposals have struggled to do justice to this variety. To our knowledge, there is to date no comprehensive overview of meditation techniques spanning all major traditions. The present studies aimed at providing such a comprehensive list of meditation techniques. Methods In a qualitative study, we compiled a collection of 309 meditation techniques through a literature search and interviews with 20 expert meditators. Then, we reduced this collection to 50 basic meditation techniques. In a second, quantitative study, 635 experienced meditators from a wide range of meditative backgrounds indicated how much experience they had with each of these 50 meditation techniques. Results Meditators’ responses indicated that our choice of techniques had been adequate and only two techniques had to be added. Our additional statistical and cluster analyses illustrated preferences for specific techniques across and within diverse traditions as well as sets of techniques commonly practiced together. Body-centered techniques stood out in being of exceptional importance to all meditators. Conclusions In conclusion, we found an amazing variety of meditation techniques, which considerably surpasses previous collections. Our selection of basic meditation techniques might be of value for future scientific investigations and we encourage researchers to use this set.

scholarly journals Software Benchmark—Classification Tree Algorithms for Cell Atlases Annotation Using Single-Cell RNA-Sequencing Data

2021 ◽  
Vol 12 (2) ◽  
pp. 317-334
Author(s):  
Omar Alaqeeli ◽  
Li Xing ◽  
Xuekui Zhang
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Classification Tree ◽  
Area Under The Curve ◽  
Data Sets ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Tree Algorithms ◽  
R Packages

Classification tree is a widely used machine learning method. It has multiple implementations as R packages; rpart, ctree, evtree, tree and C5.0. The details of these implementations are not the same, and hence their performances differ from one application to another. We are interested in their performance in the classification of cells using the single-cell RNA-Sequencing data. In this paper, we conducted a benchmark study using 22 Single-Cell RNA-sequencing data sets. Using cross-validation, we compare packages’ prediction performances based on their Precision, Recall, F1-score, Area Under the Curve (AUC). We also compared the Complexity and Run-time of these R packages. Our study shows that rpart and evtree have the best Precision; evtree is the best in Recall, F1-score and AUC; C5.0 prefers more complex trees; tree is consistently much faster than others, although its complexity is often higher than others.

scholarly journals Protest Event Analysis: Developing a Semiautomated NLP Approach

2021 ◽  
pp. 000276422110216
Author(s):  
Jasmine Lorenzini ◽  
Hanspeter Kriesi ◽  
Peter Makarov ◽  
Bruno Wüest
Keyword(s):  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Event Analysis ◽  
Validity And Reliability ◽  
Multiple Sources ◽  
Social Scientists ◽  
Extensive Discussion ◽  
Computational Tools ◽  
News Sources

Protest event analysis is a key method to study social movements, allowing to systematically analyze protest events over time and space. However, the manual coding of protest events is time-consuming and resource intensive. Recently, advances in automated approaches offer opportunities to code multiple sources and create large data sets that span many countries and years. However, too often the procedures used are not discussed in details and, therefore, researchers have a limited capacity to assess the validity and reliability of the data. In addition, many researchers highlighted biases associated with the study of protest events that are reported in the news. In this study, we ask how social scientists can build on electronic news databases and computational tools to create reliable PEA data that cover a large number of countries over a long period of time. We provide a detailed description our semiautomated approach and we offer an extensive discussion of potential biases associated with the study of protest events identified in international news sources.

scholarly journals Selection of Tree Nut Allergen Peptide Markers: A Need for Improved Protein Sequence Databases

2019 ◽  
Vol 102 (5) ◽  
pp. 1263-1270 ◽  
Author(s):  
Weili Xiong ◽  
Melinda A McFarland ◽  
Cary Pirone ◽  
Christine H Parker
Keyword(s):  
Food Allergen ◽  
Protein Sequence ◽  
Sequence Information ◽  
Sequencing Data ◽  
Reference Tree ◽  
Candidate Peptide ◽  
Tree Nut ◽  
Allergen Detection ◽  
Sequence Databases ◽  
Selection Of

Abstract Background: To effectively safeguard the food-allergic population and support compliance with food-labeling regulations, the food industry and regulatory agencies require reliable methods for food allergen detection and quantification. MS-based detection of food allergens relies on the systematic identification of robust and selective target peptide markers. The selection of proteotypic peptide markers, however, relies on the availability of high-quality protein sequence information, a bottleneck for the analysis of many plant-based proteomes. Method: In this work, data were compiled for reference tree nut ingredients and evaluated using a parsimony-driven global proteomics workflow. Results: The utility of supplementing existing incomplete protein sequence databases with translated genomic sequencing data was evaluated for English walnut and provided enhanced selection of candidate peptide markers and differentiation between closely related species. Highlights: Future improvements of protein databases and release of genomics-derived sequences are expected to facilitate the development of robust and harmonized LC–tandem MS-based methods for food allergen detection.

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