DeepInsight-3D architecture for anti-cancer drug response prediction with deep-learning on multi-omics
Modern oncology offers a wide range of treatments and therefore choosing the best option
for particular patient is very important for optimal outcome. Multi-omics profiling in …
for particular patient is very important for optimal outcome. Multi-omics profiling in …
HybridDBRpred: improved sequence-based prediction of DNA-binding amino acids using annotations from structured complexes and disordered proteins
Current predictors of DNA-binding residues (DBRs) from protein sequences belong to two
distinct groups, those trained on binding annotations extracted from structured protein-DNA …
distinct groups, those trained on binding annotations extracted from structured protein-DNA …
Enhanced analysis of tabular data through Multi-representation DeepInsight
Tabular data analysis is a critical task in various domains, enabling us to uncover valuable
insights from structured datasets. While traditional machine learning methods can be used …
insights from structured datasets. While traditional machine learning methods can be used …
GMean—a semi-supervised GRU and K-mean model for predicting the TF binding site
CW Chuah, W He, DS Huang - Scientific Reports, 2024 - nature.com
The transcription factor binding site is a deoxyribonucleic acid sequence that binds to
transcription factors. Transcription factors are proteins that regulate the transcription gene …
transcription factors. Transcription factors are proteins that regulate the transcription gene …
Isolation, characterization and therapeutic evaluation of a new Acinetobacter virus Abgy202141 lysing Acinetobacter baumannii
X Tian, X Liu, J Zhou, L Wang, Q Wang, X Qi… - Frontiers in …, 2024 - frontiersin.org
Acinetobacter baumannii is an opportunistic pathogen that easily resists currently available
antibiotics. Phages are considered alternative therapeutic agents to conventional antibiotics …
antibiotics. Phages are considered alternative therapeutic agents to conventional antibiotics …
Applications of different machine learning methods on nuclear charge radius estimations
Theoretical models come into play when the radius of nuclear charge, one of the most
fundamental properties of atomic nuclei, cannot be measured using different experimental …
fundamental properties of atomic nuclei, cannot be measured using different experimental …
Integrating reduced amino acid composition into PSSM for improving copper ion-binding protein prediction
S Liu, Y Liang, J Li, S Yang, M Liu, C Liu… - International Journal of …, 2023 - Elsevier
Copper ion-binding proteins play an essential role in metabolic processes and are critical
factors in many diseases, such as breast cancer, lung cancer, and Menkes disease. Many …
factors in many diseases, such as breast cancer, lung cancer, and Menkes disease. Many …
Deep-GAN: an improved model for thyroid nodule identification and classification
R Srivastava, P Kumar - Neural Computing and Applications, 2024 - Springer
Tailoring a deep convolutional neural network (DCNN) is a tedious and time-consuming task
in the field of medical image analysis. In this research paper, Deep-generative adversial …
in the field of medical image analysis. In this research paper, Deep-generative adversial …
[HTML][HTML] Accurately Identifying Sound vs. Rotten Cranberries Using Convolutional Neural Network
Cranberries, native to North America, are known for their nutritional value and human health
benefits. One hurdle to commercial production is losses due to fruit rot. Cranberry fruit rot …
benefits. One hurdle to commercial production is losses due to fruit rot. Cranberry fruit rot …
DWFL: Enhancing Federated Learning through Dynamic Weighted Averaging
Federated Learning (FL) is a distributed learning technique that maintains data privacy by
providing a decentralized training method for machine learning models using distributed big …
providing a decentralized training method for machine learning models using distributed big …