Efficient Algorithms for GPU Accelerated Evaluation of the DFT Exchange-Correlation Functional by Ryan Stocks (16867476)

“…In this work, we present a comparative study of four GPU-accelerated algorithms for evaluating the KS-DFT exchange–correlation (XC) potential with an atom-centered Gaussian basis. …”

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) by Santhosh Kumar Rajamani (13023678)

Algorithm framework. by Zongjin Li (38031)

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Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…Among such patterns, <i>mutual exclusivity</i> has been employed by several recent methods that have shown its effectiveness in characterizing gene sets associated to cancer. Mutual exclusivity arises because of the complementarity, at the functional level, of alterations in genes which are part of a group (e.g., a <i>pathway</i>) performing a given function. …”

Model training accuracy for Random Forest (RF), Multilayer Perceptron (MLP), and Radial Basis Function (RBF) algorithms by adding variables based on the correlation results. by Mohsen Yoosefzadeh-Najafabadi (6917399)

Testing performance comparison for different algorithms. by Roberto Bárcenas (13924220)

Training performance comparison for different algorithms. by Roberto Bárcenas (13924220)

Verification of the in-line PS function. by Raul Castañeda (13932971)

Available functions in the utility package. by Raul Castañeda (13932971)

MSVM-RFE algorithm for screening key genes. by Ya xi Zhu (11624730)

The SVM objective function minimization against iterations. by Ali Ahmed (2567584)

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DataSheet1_A self-training subspace clustering algorithm based on adaptive confidence for gene expression data.PDF by Dan Li (106345)

“…The superiority of the proposed SSCAC algorithm is mainly reflected in the following aspects. 1) In order to improve the discriminative property of gene expression data, the low-rank representation with distance penalty is used to mine the potential subspace structure of data. 2) Considering the problem of mislabeling in self-training, a semi-supervised clustering objective function with label confidence is proposed, and a self-training subspace clustering framework is constructed on this basis. 3) In order to mitigate the negative impact of mislabeled data, an adaptive adjustment strategy based on gravitational search algorithm is proposed for label confidence. …”

Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

Probably pathogenic variants (algorithms). by Felipe Fidalgo (642532)

Available functions in the phase-shifting package. by Raul Castañeda (13932971)

Available functions in the numerical propagation package. by Raul Castañeda (13932971)

Available functions in the phase reconstruction package. by Raul Castañeda (13932971)

Comparison of results of different algorithms. by Zhongzhong Guo (12133402)

Subjects: “…differentially expressed genes…”

Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

“…</p> <p>The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. …”

The eVIP algorithm uses RNA-seq data to predict the function of somatic mutations. by Alexis M. Thornton (11068403)

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