Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm by Hussein Ali Bardan (21976208)

“…In this work, we propose a novel framework that integrates </p><p dir="ltr">Convolutional Neural Networks (CNNs) for image classification and a binary Grey Wolf Optimization (GWO) </p><p dir="ltr">algorithm for feature selection. …”

DataSheet1_Comprehensive analysis of immune-related gene signature based on ssGSEA algorithms in the prognosis and immune landscape of hepatocellular carcinoma.ZIP by Liangliang Wang (580395)

“…This study aimed to distinguish patients with HCC having distinct tumour immune microenvironment (TIME) features and construct an immune-related gene signature (IRGs) to assess prognosis and provide a basis for personalised therapies.…”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…This work mainly focuses on the following aspects: (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks. (2) Isolated genes were properly processed by the IDS to optimize the network structure. (3) The performance of IMBDANET was assessed with extensive experiments. …”

Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm by Interdis Sci Comp Life Sci (7335308)

“…This work mainly focuses on the following aspects:</p><p dir="ltr"> (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks.…”

datasheet1_Graph Neural Networks for Maximum Constraint Satisfaction.pdf by Jan Tönshoff (10192709)

Breast cancer specific subnetwork. by Bengi Ruken Yavuz (21983004)

Table4_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table3_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table2_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table5_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table1_Identifying Key MicroRNA Signatures for Neurodegenerative Diseases With Machine Learning Methods.XLSX by ZhanDong Li (11653330)

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf by Muhammad Awais (263096)

“…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …”

Supplementary Material for: Introducing exome sequencing as part of the diagnostic algorithm for pediatric nephrology patients in Bulgaria - a single-center experience by Beltcheva O. (18262381)

“…Given the large number of genes involved in kidney disease, introducing next generation sequencing with extended gene panels as part of the diagnostic algorithm presents a viable solution. …”

DataSheet2_Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models.xlsx by Haoliang Fan (7868108)

“…<p>Epigenetic clock, a highly accurate age estimator based on DNA methylation (DNAm) level, is the basis for predicting mortality/morbidity and elucidating the molecular mechanism of aging, which is of great significance in forensics, justice, and social life. …”

DataSheet1_Chronological Age Prediction: Developmental Evaluation of DNA Methylation-Based Machine Learning Models.pdf by Haoliang Fan (7868108)

“…<p>Epigenetic clock, a highly accurate age estimator based on DNA methylation (DNAm) level, is the basis for predicting mortality/morbidity and elucidating the molecular mechanism of aging, which is of great significance in forensics, justice, and social life. …”

Table_2_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…</p>Conclusions<p>A new gene signature for IA based on ICD features was created. …”

Image_3_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…</p>Conclusions<p>A new gene signature for IA based on ICD features was created. …”

Image_4_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…</p>Conclusions<p>A new gene signature for IA based on ICD features was created. …”

Table_1_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…</p>Conclusions<p>A new gene signature for IA based on ICD features was created. …”

Image_2_An immunogenic cell death-related regulators classification patterns and immune microenvironment infiltration characterization in intracranial aneurysm based on machine lea... by Mirzat Turhon (12220898)

“…</p>Conclusions<p>A new gene signature for IA based on ICD features was created. …”