Microbial Keystone Taxa Identification in Global Wastewater Treatment Plants Based on Deep Learning by Sen Wang (135167)

“…In this work, we applied this framework to the high-throughput sequencing of the global wastewater treatment sample and identified 61 candidate taxa as the keystones for the wastewater treatment process. We found that the temperature and dissolved oxygen are the primary factors influencing the keystone taxa. …”

Microbial Keystone Taxa Identification in Global Wastewater Treatment Plants Based on Deep Learning by Sen Wang (135167)

“…In this work, we applied this framework to the high-throughput sequencing of the global wastewater treatment sample and identified 61 candidate taxa as the keystones for the wastewater treatment process. We found that the temperature and dissolved oxygen are the primary factors influencing the keystone taxa. …”

Microbial Keystone Taxa Identification in Global Wastewater Treatment Plants Based on Deep Learning by Sen Wang (135167)

“…In this work, we applied this framework to the high-throughput sequencing of the global wastewater treatment sample and identified 61 candidate taxa as the keystones for the wastewater treatment process. We found that the temperature and dissolved oxygen are the primary factors influencing the keystone taxa. …”

Microbial Keystone Taxa Identification in Global Wastewater Treatment Plants Based on Deep Learning by Sen Wang (135167)

“…In this work, we applied this framework to the high-throughput sequencing of the global wastewater treatment sample and identified 61 candidate taxa as the keystones for the wastewater treatment process. We found that the temperature and dissolved oxygen are the primary factors influencing the keystone taxa. …”

Microbial Keystone Taxa Identification in Global Wastewater Treatment Plants Based on Deep Learning by Sen Wang (135167)

“…In this work, we applied this framework to the high-throughput sequencing of the global wastewater treatment sample and identified 61 candidate taxa as the keystones for the wastewater treatment process. We found that the temperature and dissolved oxygen are the primary factors influencing the keystone taxa. …”

Overview of the algorithmic approach and its place in the hypothesis generation toolkit. by Braden T. Tierney (8822813)

Data_Sheet_1_Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre.PDF by Benjamin Hunter (2885960)

Identification of failure conditions. by Anees ul Husnain (18017648)

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

“…</p>Methods<p>To address these challenges, we propose a novel AI-driven framework that incorporates two key methodological innovations: CardioSpectra, a structured sparse inference model, and Risk-Stratified Exertional Embedding (RSEE), a domain-specific representation learning strategy. …”

Accession list and passport data. by Diego Felipe Conejo-Rodríguez (18495740)

“…<div><p>High-throughput phenotyping brings new opportunities for detailed genebank accessions characterization based on image-processing techniques and data analysis using machine learning algorithms. …”

iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier by Lijun Dou (9554059)

“…Lysine glutarylation is a newly reported post-translational modification (PTM) that plays significant roles in regulating metabolic and mitochondrial processes. Accurate identification of protein glutarylation is the primary task to better investigate molecular functions and various applications. …”

Data_Sheet_1_Identification of Snails and Schistosoma of Medical Importance via Convolutional Neural Networks: A Proof-of-Concept Application for Human Schistosomiasis.pdf by Krti Tallam (11135877)

Data_Sheet_4_Identification of a Three-Glycolysis-Related lncRNA Signature Correlated With Prognosis and Metastasis in Clear Cell Renal Cell Carcinoma.xlsx by Tinghao Li (10507577)

Data_Sheet_3_Identification of a Three-Glycolysis-Related lncRNA Signature Correlated With Prognosis and Metastasis in Clear Cell Renal Cell Carcinoma.xlsx by Tinghao Li (10507577)

Data_Sheet_5_Identification of a Three-Glycolysis-Related lncRNA Signature Correlated With Prognosis and Metastasis in Clear Cell Renal Cell Carcinoma.xlsx by Tinghao Li (10507577)

Data_Sheet_2_Identification of a Three-Glycolysis-Related lncRNA Signature Correlated With Prognosis and Metastasis in Clear Cell Renal Cell Carcinoma.xlsx by Tinghao Li (10507577)

Data_Sheet_1_Identification of a Three-Glycolysis-Related lncRNA Signature Correlated With Prognosis and Metastasis in Clear Cell Renal Cell Carcinoma.xls by Tinghao Li (10507577)

Data_Sheet_1_Identification of diagnostic gene biomarkers and immune infiltration in patients with diabetic kidney disease using machine learning strategies and bioinformatic analy... by Shaojie Fu (9658334)

Phenomic and classical descriptors. by Diego Felipe Conejo-Rodríguez (18495740)

“…<div><p>High-throughput phenotyping brings new opportunities for detailed genebank accessions characterization based on image-processing techniques and data analysis using machine learning algorithms. …”

Data_Sheet_3_Multisite Comparison of MRI Defacing Software Across Multiple Cohorts.docx by Athena E. Theyers (10186742)