Data_Sheet_1_A Greedy Algorithm-Based Stem Cell LncRNA Signature Identifies a Novel Subgroup of Lung Adenocarcinoma Patients With Poor Prognosis.PDF by Seema Khadirnaikar (9227318)

“…A notable result observed was high infiltration of T cells and a higher level of neopeptides in uLUAD patients, making these patients an optimal candidate for immunotherapy. Further, feature selection using greedy algorithm identified 17-hESC-lncRNAs signature, which showed significant consistency with 198 hESC-lncRNAs–based classification, and identified a group of patients with high stem cell–like characteristic in the 10 most common cancer types and CCLE cell lines. …”

Data_Sheet_2_A Greedy Algorithm-Based Stem Cell LncRNA Signature Identifies a Novel Subgroup of Lung Adenocarcinoma Patients With Poor Prognosis.xlsx by Seema Khadirnaikar (9227318)

“…A notable result observed was high infiltration of T cells and a higher level of neopeptides in uLUAD patients, making these patients an optimal candidate for immunotherapy. Further, feature selection using greedy algorithm identified 17-hESC-lncRNAs signature, which showed significant consistency with 198 hESC-lncRNAs–based classification, and identified a group of patients with high stem cell–like characteristic in the 10 most common cancer types and CCLE cell lines. …”

Network propagation identifies ageing-associated genes as well as genes distinguishing prostate tumors of different grades. by Konstantina Charmpi (9901053)

A secondary structure model of the effects of <i>Cis</i> mutation on splicing efficiency. by Idan Frumkin (3122832)

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC‑1 Cell Line by Zhijing Tan (1314216)

“…Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. …”

Methodology block diagram. by Gahao Chen (21688843)

“…Six machine learning algorithms - Random Forest (RF), AdaBoost, Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Tabular Prior-data Fitted Network version 2.0 (TabPFN-V2) - were implemented with five-fold cross-validation to optimize model hyperparameters. …”

Data_Sheet_1_A hybrid energy-based and AI-based screening approach for the discovery of novel inhibitors of JAK3.pdf by Juying Wei (13815403)

“…This article presents a structure-based hybrid high-throughput virtual screening (HTVS) protocol as well as the DeepDock algorithm, which is based on geometric deep learning. …”

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

Data Sheet 1_Discovery of a DNA repair-associated radiosensitivity index for predicting radiotherapy efficacy in breast cancer.docx by Jianguang Lin (13032527)

“…Accurately predicting tumor radiosensitivity is critical for optimizing therapeutic outcomes and personalizing treatment strategies. …”