Preprints (not yet peer-reviewed)

22 downloads
108 views

Background. Although pathogenic Gram-negative bacteria lack their own ubiquitination machinery, they have evolved or acquired virulence effectors that can manipulate the host ubiquitination process through structural and/or functional mimicry of host machinery....

["Bioinformatics","Computational Biology","Microbiology","Infectious Diseases","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.27292v1
1,050 downloads
1,718 views

Gene expression is the fundamental level at which the result of various genetic and regulatory programs are observable. The measurement of transcriptome-wide gene expression has convincingly switched from microarrays to sequencing in a matter of years. RNA sequencing...

["Bioinformatics","Computational Biology","Genomics","Data Science"]
doi:10.7287/peerj.preprints.27283v1
148 downloads
205 views

Possible combinations of inputs in the order of 10100 can fire (axonal spike or action potential) a neuron that has nearly 104 inputs (dendritic spines). This extreme degeneracy of inputs that can fire a neuron is associated with significant loss of information...

["Biophysics","Computational Biology","Neuroscience","Cognitive Disorders","Computational Science"]
doi:10.7287/peerj.preprints.27228v3
113 downloads
255 views

Open-ended evolution researchers seek to create systems that continually produce new evolutionary outcomes, attempting to reflect the power and diversity of evolution in nature. The specific metrics used (novelty, complexity, diversity, etc) vary by researcher,...

["Computational Biology","Evolutionary Studies"]
doi:10.7287/peerj.preprints.27246v2
92 downloads
112 views

Building more open-ended evolutionary systems can simultaneously advance our understanding of biology, artificial life, and evolutionary computation. In order to do so, however, we need a way to determine when we are moving closer to this goal. We propose a set...

["Computational Biology","Adaptive and Self-Organizing Systems","Agents and Multi-Agent Systems","Scientific Computing and Simulation"]
doi:10.7287/peerj.preprints.27249v3
35 downloads
75 views

Describing cell morphology is a tricky task, prone to misinterpretation due to subjective nature of the human observer and his vocabulary limitations. Consequently, these limitations actuate prevalence of non-formalized, statistically unverifiable language use....

["Bioinformatics","Cell Biology","Computational Biology","Marine Biology","Mathematical Biology"]
doi:10.7287/peerj.preprints.27271v2
22 downloads
64 views

Background. Following recent advances in bioimaging, high-resolution 3D models of biological structures are now generated rapidly and at low-cost. To utilise this data to address evolutionary and ecological questions, an array of tools has been developed to conduct...

["Computational Biology","Evolutionary Studies","Mathematical Biology"]
doi:10.7287/peerj.preprints.27270v1
24 downloads
82 views

The fractal formalism in combination with linear image analysis enables statistically significant description and classification of “irregular” (in terms of Euclidean geometry) shapes, such as, outlines of in vitro flattened cells. We developed an optimal model...

["Bioinformatics","Cell Biology","Computational Biology","Marine Biology"]
doi:10.7287/peerj.preprints.27258v1
66 downloads
249 views

Translational models that utilize omics data generated in in vitro studies to predict the drug efficacy of anti-cancer compounds in patients are highly distinct, which complicates the benchmarking process for new computational approaches. In reaction to this, we...

["Computational Biology","Genomics","Statistics","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.27256v1
341 downloads
802 views

Pathway and cell-type signatures are patterns present in transcriptome data that are associated with biological processes or phenotypic consequences. These signatures result from specific cell-type and pathway expression, but can require large transcriptomic compendia...

["Bioinformatics","Computational Biology","Genomics","Data Mining and Machine Learning"]
doi:10.7287/peerj.preprints.27229v1
178 downloads
408 views

One overarching principle of eukaroytic development is the generative spatial emergence and self-organization of cell populations. As cells divide and differentiate, they and their descendants form a spatiotemporally explicit and increasingly compartmentalized...

["Bioinformatics","Computational Biology","Developmental Biology"]
doi:10.7287/peerj.preprints.26587v2
8,152 downloads
13,049 views

Spreadsheets are widely used software tools for data entry, storage, analysis, and visualization. Focusing on the data entry and storage aspects, this paper offers practical recommendations for organizing spreadsheet data to reduce errors and ease later analyses....

["Computational Biology","Science and Medical Education","Statistics","Computational Science","Data Science"]
doi:10.7287/peerj.preprints.3183v2
192 downloads
344 views

The general purpose of this paper is to build up on our understanding of the basic mathematical principles that underlie the emergence of synchronous biological rhythms, in particular, the circadian clock. To do so, we study the role that the coupling strength,...

["Computational Biology","Mathematical Biology"]
doi:10.7287/peerj.preprints.26447v2
91 downloads
355 views

Ecological communities are composed of a combination of core species that maintain local viable populations and transient species that occur infrequently due to dispersal from surrounding regions. Preliminary work indicates that while core and transient species...

["Computational Biology","Ecology"]
doi:10.7287/peerj.preprints.27158v1
41 downloads
75 views

The Bertalanffy-Pütter growth model describes mass m at age t by means of the differential equation dm/dt = p⋅ma−q⋅mb. The special case using the Bertalanffy exponent-pair a=2/3 and b=1 is most common (it corresponds to the von Bertalanffy growth function VBGF...

["Aquaculture, Fisheries and Fish Science","Computational Biology","Marine Biology","Mathematical Biology","Computational Science"]
doi:10.7287/peerj.preprints.27152v1
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