Comparison of the smooth-index (‘SI’) algorithm with feedback arc set (‘FAS’) sorting. by Alexander Borst (32619)

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Application of the smooth-index algorithm to the single-column connectome of the Drosophila optic lobe. by Alexander Borst (32619)

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Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

“…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

“…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”

Execution Steps of the EOF Algorithm. by Zezhi Lin (22521663)

The number of inactive nodes as a function of time steps at higher values of <i>P</i> and <i>α</i> in (a) a random network and (b) a scale-free network. by Waseem Al-Aqqad (14123917)

The main steps of the general algorithm. by Dror Mughaz (18017583)

Internal cross-validation step of S component in 3Mont. by Miray Unlu Yazici (14792680)

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If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…More specifically, we plot the <i>R</i>² of the best linear model minus the <i>R</i>² of the best quadratic, where “best” refers to the model identified by the corresponding Metropolis algorithm over its finite runtime (10000 steps). (B) Nevertheless, even when the linear algorithm loses in <i>R</i>², the grouping it identifies can be a better representation of the underlying ground truth. …”

Application of the smooth-index to bandwidth-limited matrices (A,B) and to block-diagonal matrices (C,D). by Alexander Borst (32619)

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Steps in the proposed Apriori algorithm. by Yongkang Ding (21807539)

Step by step workflow for PRLF model training and data scoring. by John Prindle (10774286)

Flowchart of step() function. by Raed Alharthi (18340157)

Sorting time is nominally similar between automated and manual sorting, but automation enables walk-away functionality. by Diane M. Wiener (1956583)

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Preservation analysis of co-expressed modules of control networks were tested in the stress condition based on the median rank (A) and Zsummary (B) algorithms. by Bahman Panahi (7323578)

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Python-based Monte Carlo Simulation Tool by Yangfan Jiang (9372782)

The collective motion, collision avoidance, and CMCA score of the VCMCA algorithm, VCMCA algorithm without CA, and random walk over the simulation steps for <i>n</i> = 30 repetitio... by David L. Krongauz (15447260)

(a-c) Sampling event times with an intensity function . by Gerrit Großmann (9585147)

User options and main steps of the generative algorithm. by Diana C. de Oliveira (9220729)