Cluster distance and size for AC STORM data. حسب Lingxia Qiao (19996756)

Co-diagnostic gene screening and machine learning modelling. حسب Juntu Li (20411498)

Selection and analysis of characteristic genes for non-obstructive azoospermia (NOA). حسب Qiang Ling (11415101)

The immune microenvironment association of CENPA in cancers. حسب Hengrui Liu (2059750)

Construction of PPI network and screening of hub genes. حسب Lei Wang (6656)

Evaluation of the relationship between KLF4 expression and cancer-associated fibroblast (CAF) infiltration. حسب Shoukai Yu (5003270)

Analysis of immune system infiltration across the high and low groups in the combined datasets (CIBERSORTx). حسب Mian Wang (153332)

SHAP values for chromatin-associated proteins profiled in Wang et al. [22] (A) Chromatin-associated proteins and histone marks relevant for this model. حسب Kashyap Chhatbar (9515350)

SHAP values for SET1A, H3K4me3 and ZC3H4. حسب Kashyap Chhatbar (9515350)

Feature mapping for vowel-e. حسب Gaurav Datkhile (22662871)

Feature mapping for vowel-a. حسب Gaurav Datkhile (22662871)

Feature mapping for vowel-o. حسب Gaurav Datkhile (22662871)

Confusion Matrix for result analysis. حسب Gaurav Datkhile (22662871)

System block diagram. حسب Gaurav Datkhile (22662871)

During non-lethal stress, non-canonical cleavage of CASP7 occurs at calpain cleavage sites; related to Fig 4. حسب Gayathri Samarasekera (2610199)

Comparison of immune cell infiltration between high-risk and low-risk sample groups. حسب Changquan Shang (21647625)

Calculating the TAMs-associated score. حسب Changquan Shang (21647625)

PLOS One data. حسب Ayşenur Eser (21713911)

"…<div><p>Automated detection of emotional states through brain-computer interfaces (BCIs) offers significant potential for enhancing user experiences and personalizing services across domains such as mental health, adaptive learning and interactive entertainment. Within this advancing field, the aim of this study was to test the feasibility of a functional near-infrared spectroscopy (fNIRS)-based BCI system for accurate prediction and objective identification of three fundamental emotional states that involved positive, negative and neutral conditions. …"

Presentation of the DySCo framework. حسب Giuseppe de Alteriis (20846230)

"…<p>A: What is dynamic Functional Connectivity: i) We can start from any set of brain recordings, where each signal is referred to a brain location (e.g. fMRI, EEG, intracranial recordings in rodents, and more). ii) “Static” Functional Connectivity (FC) is a matrix where each entry is a time aggregated functional measure of interaction between two regions, for example, the Pearson Correlation Coefficient. iii) Dynamic Functional Connectivity (dFC) is a FC matrix (that can be calculated in different ways, see below) that changes with time, under the assumption that patterns of brain interactions are non-stationary. …"

Overview of data analysis. حسب Mehrnaz Shoushtarian (6411299)