The results of LASSO regression algorithm. by Xue Fu (549661)

The algorithm is designed to identify patterns in the treatment dataset. by Belén Otero-Carrasco (21262360)

“…<p>This process involves two key functions. First, from lines 1 to 8, the algorithm identifies amino acids that meet the occurrence threshold, starting with patterns of length 1. …”

Data from: Structural and Functional Analysis of Multi-interface Domains by ZHAO Liang (8657694)

“…This work applies graph theory and algorithms to discover fingerprints for the multiple interfaces of a domain and to establish associations between the interfaces and functions, based on a huge set of multi-interface proteins from PDB. …”

Depiction of how the label of is assigned as a function of whether are identical (row =), nested (rows ), or partially overlapping (row “else”), and as a function of the labels of... by Jordan Moutet (21800145)

Analysis of the limit cases of the sampling function. by Greta Grassmann (12418506)

Subjects:

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

“…We then evaluate the ability to identify lead compounds among a large chemical space for the proposed flexible receptor docking algorithm using a subset of the DUD-E containing receptor targets MCR, GCR, and ANDR. …”

Flexible CDOCKER: Hybrid Searching Algorithm and Scoring Function with Side Chain Conformational Entropy by Yujin Wu (2901128)

“…We then evaluate the ability to identify lead compounds among a large chemical space for the proposed flexible receptor docking algorithm using a subset of the DUD-E containing receptor targets MCR, GCR, and ANDR. …”

Table1_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…Furthermore, some quantitative rules were established to identify the potential subcellular localizations of proteins. As the first prediction model that uses direct protein annotation information (i.e., functional features) and STRING-based protein–protein interaction network (i.e., network features), our computational model can help promote the development of predictive technologies on subcellular localizations and provide a new approach for exploring the protein subcellular localization patterns and their potential biological importance.…”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Our algorithms process large data sets within a minute. by Manu Aggarwal (15990691)

(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

Subjects:

Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

The proposed method for protein function prediction. by Seyyede Fatemeh Seyyedsalehi (10196767)

Subjects:

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

“…Subsequently, consensus variants predicted as pathogenic undergo further evaluation through a web server employing an algorithm based on structural homology. The resulting 11 variants are then validated using in silico tools that assess variant effects based on genetic and molecular data. …”

Pairwise alignment results from human proteins and <i>H</i>. <i>pylori</i> proteins using Blosum 62 and PM250 algorithms. by Andrés Sánchez Caraballo (15354081)

Curves of sigmoid functions used in our proposed algorithm. by Binh Thanh Dang (12368831)

“…<p>Curves of sigmoid functions used in our proposed algorithm.</p>…”

The GOR4 and SOPMA algorithm findings. by Ahmad Abdullah Mahdeen (19704401)

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Table2_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…Furthermore, some quantitative rules were established to identify the potential subcellular localizations of proteins. As the first prediction model that uses direct protein annotation information (i.e., functional features) and STRING-based protein–protein interaction network (i.e., network features), our computational model can help promote the development of predictive technologies on subcellular localizations and provide a new approach for exploring the protein subcellular localization patterns and their potential biological importance.…”

Table3_Predicting Human Protein Subcellular Locations by Using a Combination of Network and Function Features.XLSX by Lei Chen (54296)

“…Furthermore, some quantitative rules were established to identify the potential subcellular localizations of proteins. As the first prediction model that uses direct protein annotation information (i.e., functional features) and STRING-based protein–protein interaction network (i.e., network features), our computational model can help promote the development of predictive technologies on subcellular localizations and provide a new approach for exploring the protein subcellular localization patterns and their potential biological importance.…”