All other elements of the figures remain unchanged while the interpretation of the results remains valid. The errored and corrected legends in the three figures were listed as followed: [Table presented] The authors would like to apologise for any inconvenience caused....
To answer these questions, we need to unravel the neural network internal operations; a challenging problem which has recently attracted considerable attention in the deep learning community50–55. The difficulty of this task lies in both the tendency of deep learning models to represent the ...
Recently, StyleGAN has been introduced to unravel high-level attributes with latent factors44. As the UIDT aims to translate between two different imaging modalities, stochastic effects in the generated image domain can provide controllability to the DL networks, ensuring improved performance, ...
To unravel mechanisms governing glycosylation regulation, robust and high-throughput quantification methods are required. So far, most of the quantitative glycoproteomics studies have relied on label-free approaches, which come with inherent limitations as these strategies are incompatible with the different...
it is challenging to unravel the intricate mechanisms underlying the network’s weights and the activation values of hidden neurons in relation to the problem at hand. This sets ANNs apart from classical statistical models, as determining the relationship between each explanatory variable and the depen...
Phylogenetic trees built using CNAs offer insights into the heterogeneity and evolutionary dynamics of genetic alterations during cancer initiation and progression and have been used to unravel ITH, decipher the molecular mechanisms of metastasis, understand treatment resistance, and inform early cancer detec...
STdGCN has the potential to greatly enhance our understanding of tissue spatial architecture and provide invaluable support for downstream analyses at the cellular level. With its ability to unravel the intricate composition of cell types within ST datasets, STdGCN opens new avenues for exploring the...
Over the last decades, extensive research has been conducted to unravel the molecular, cellular and immunological mechanisms involved in cancer development. Especially the extensive use of next-generation sequencing (NGS) technologies enabled a progressively more cost-effective approach for the discovery of...
To this end, we performed unsupervised classification of proteins and metabolites in mice during cardiac remodeling using two innovative deep learning (DL) approaches. First, long short-term memory (LSTM)-based variational autoencoder (LSTM-VAE) was trained on time-series numeric data. The low-...
However, their internal composition is often difficult to unravel. Functional LTRs must always contain three regions important for the life cycle of the entire TE. These are known as U3, R and U5, and can be determined experimentally [17]. U3 is known to bind regulatory proteins important ...