Preprints (not yet peer-reviewed)

6 downloads
33 views

With an unprecedented growth in the biomedical literature, keeping up to date with the new developments presents an immense challenge. Publications are often studied in isolation of the established literature, with interpretation being subjective and often introducing...

["Bioinformatics","Algorithms and Analysis of Algorithms","Data Mining and Machine Learning","Software Engineering","Visual Analytics"]
doi:10.7287/peerj.preprints.26869v1
127 downloads
720 views

A new layer of complexity, constituted of networks of information token recurrence, has been identified in socio-technical systems such as the Wikipedia online community and the Zooniverse citizen science platform. The identification of this complexity reveals...

["Data Mining and Machine Learning","Data Science","Network Science and Online Social Networks","Social Computing","World Wide Web and Web Science"]
doi:10.7287/peerj.preprints.2789v2
27 downloads
169 views

We present PromoterPredict, a dynamic multiple regression approach to predict the strength of Escherichia coli promoters binding the σ70 factor of RNA polymerase. σ70 promoters are ubiquitously used in recombinant DNA technology, but characterizing their strength...

["Bioengineering","Bioinformatics","Biotechnology","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26759v2
122 downloads
257 views

High-throughput sequencing of environmental DNA (eDNA) offers a simple and cost-effective solution for marine biodiversity assessments. Yet several analytical challenges remain, including the incorporation of statistical inference in the assignment of taxonomic...

["Biodiversity","Bioinformatics","Computational Biology","Marine Biology","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26812v1
222 downloads
470 views

Potential Natural Vegetation (PNV) is the vegetation cover in equilibrium with climate, that would exist at a given location non-impacted by human activities. PNV is useful for raising public awareness about land degradation and for estimating land potential. This...

["Biogeography","Computational Biology","Plant Science","Data Mining and Machine Learning","Spatial and Geographic Information Science"]
doi:10.7287/peerj.preprints.26811v1
115 downloads
269 views

The advent of next-generation sequencing has resulted in transcriptome-based approaches to investigate functionally significant biological components in a variety of non-model organism. This has resulted in the area of “venomics”: a rapidly growing field using...

["Bioinformatics","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26733v1
38 downloads
73 views

There are numerous models for affective states classification and social behavior description. Despite proving their reliability, some of these classifications turn out to be redundant, while others — insufficient for certain practical purposes. In this paper we...

["Psychiatry and Psychology","Science and Medical Education","Human-Computer Interaction","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26729v1
35 downloads
68 views

Nowadays, there is a large number of machine learning models that could be used for various areas. However, different research targets are usually sensitive to the type of models. For a specific prediction target, the predictive accuracy of a machine learning model...

["Artificial Intelligence","Data Mining and Machine Learning","Data Science"]
doi:10.7287/peerj.preprints.26714v1
240 downloads
417 views

Random forest and similar Machine Learning techniques are already used to generate spatial predictions, but spatial location of points (geography) is often ignored in the modeling process. Spatial auto-correlation, especially if still existent in the cross-validation...

["Biogeography","Soil Science","Computational Science","Data Mining and Machine Learning","Spatial and Geographic Information Science"]
doi:10.7287/peerj.preprints.26693v1
50 downloads
76 views

The classification of fresh fruits according to their ripeness is typically a subjective and tedious task; consequently, there is growing interest in the use of non-contact techniques such as those based on computer vision and machine learning. In this paper, we...

["Agricultural Science","Computational Biology","Food Science and Technology","Computational Science","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26691v1
168 downloads
377 views

Emotion expression encompasses various types of information, including face and eye movement, voice and body motion. Most of the studies in automated affective recognition use faces as stimuli, less often they include speech and even more rarely gestures. Emotions...

["Neuroscience","Human-Computer Interaction","Computational Science","Data Mining and Machine Learning","Data Science"]
doi:10.7287/peerj.preprints.26688v1
57 downloads
189 views

The analysis of microbiome dynamics would allow us to elucidate patterns within microbial community evolution; however, microbiome state-transition dynamics have been scarcely studied. This is in part because a necessary first-step in such analyses has not been...

["Bioinformatics","Computational Biology","Microbiology","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.26657v1
28 downloads
151 views

Background. The institutional affiliations and associated collaborative networks that scientists foster during their research careers are salient in the production of high quality science. The phenomenon of multiple institutional affiliations and its relationship...

["Data Mining and Machine Learning","Data Science"]
doi:10.7287/peerj.preprints.26654v1
68 downloads
122 views

Many people make their opinions available on the Internet nowadays, and researchers have been proposing methods to automate the task of classifying textual reviews as positive or negative. Usual supervised learning techniques have been adopted to accomplish such...

["Computational Linguistics","Data Mining and Machine Learning","Data Science","Natural Language and Speech","World Wide Web and Web Science"]
doi:10.7287/peerj.preprints.26618v1
85 downloads
158 views

R has many capabilities most of which are not known by many users, yet waiting to be discovered. For this reason we provide more tips on how to write really efficient code without having to program in C++, programming advice, and tips to avoid errors and numerical...

["Bioinformatics","Computational Biology","Computational Linguistics","Data Mining and Machine Learning","Data Science"]
doi:10.7287/peerj.preprints.26605v1
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