Detailed schematics of the algorithm developed to map and filter protein lists from one organism to another (ortholog identification). by Silvia Ambrós (11037668)

Detailed information of benchmark functions. by Guangwei Liu (181992)

“…In Case 1, the GJO-GWO algorithm addressed eight complex benchmark functions. …”

Generated molecular network based on differential expression of genes of SARS-CoV-2 infected (<i>in vitro</i>) airway epithelium associated with (A) ’cellular movement, hematologic... by Rajaneesh K. Gupta (11495309)

Data_Sheet_1_Adapting Community Detection Algorithms for Disease Module Identification in Heterogeneous Biological Networks.pdf by Beethika Tripathi (6451523)

“…These networks are known to be highly modular, with groups of proteins associated with specific biological functions. Human diseases often arise from the dysfunction of one or more such proteins of the biological functional group. …”

The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou. by Mengqi He (5753525)

Reprojection of the validation points (9×6 lattice points) using the models obtained from the symbolic regression algorithm on the 6 calibration patterns. by Almoctar Hassoumi (6470354)

Hist-8000 sequence similarity scores are closer to the ground truth than the corresponding Sum-of-learnt-Trigrams scores. (NW, Hist-8000) and (NW, Hist-SDM12) are both higher than... by Frixos Papadopoulos (22001664)

Signal detection algorithm adapted from [1] yields exponential distributions and unrealistic mean durations of percepts. by Quynh-Anh Nguyen (847240)

“…(Bottom) Trial-by-trial applications of the signal detection algorithm from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>] with A: <i>C</i>_<i>th</i> = 4.01 and B: <i>C</i>_<i>th</i> = 4.21 yield exponentially distributed subsequent percept durations for <i>I</i> (blue) and <i>S</i> (red). …”

Algorithmic Chronology of Freely Active Agents. by Robert J. Wagner (9857666)

Sensitivity analysis of the TV-BayesOpt algorithm performance at tracking a periodic temporal drift when the period of the drift is offset from the covariance function period anticipated by the TV-BayesOpt algorithm. by John E. Fleming (8533956)

Parselmouth for bioacoustics: automated acoustic analysis in Python by Yannick Jadoul (11498813)

“…Five years ago, the Python package Parselmouth was released to provide easy and intuitive access to all functionality in the Praat software. …”

Parameters of the test function. by Yiqiong Gao (16698968)

“…The adaptive adjustment of the transition probability effectively balances the development and exploration abilities of the algorithm. The improved flower pollination algorithm (IFPA) outperformed six classical benchmark functions that were used to verify the superiority of the improved algorithm. …”

Comparison of the top five upregulated and top five downregulated molecular function GO terms of Unipept with the molecular function GO terms from the other tools from the oral dys... by Ray Sajulga (5721518)

Effect of “nonfunctional group” on function. by Yuanchen Zhao (12905580)

Subjects:

PCA visualization of LSTM hidden layer activity of an example 7-hidden-unit network (#7). by Quan Wan (1329666)

Subjects:

2-back task structure in the Wan et al. [13] EEG study. by Quan Wan (1329666)

Subjects:

Stimulus trial-averages of EEG signal projected into UMI and PMI subspaces over a 2-delay time course (-2800ms to 3550ms relative to stimulus <i>n + 1</i> onset). by Quan Wan (1329666)

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Stimulus trial-averages of RNN hidden layer activity projected into UMI and PMI subspaces over the course of a trial (stimulus <i>n</i> to <i>delay 2</i>:<i>2</i>). by Quan Wan (1329666)

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Kaplan–Meier survival function from METABRIC (training) data. by Luke Kumar (7871492)

Table_1_Clinical Functional Seizure Score (CFSS): a simple algorithm for clinicians to suspect functional seizures.DOCX by Mohammad Dashtkoohi (15417886)