AIPs-SnTCN: Predicting anti-inflammatory peptides using fastText and transformer encoder-based hybrid word embedding with self-normalized temporal …
Inflammation is a biologically resistant response to harmful stimuli, such as infection,
damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic …
damaged cells, toxic chemicals, or tissue injuries. Its purpose is to eradicate pathogenic …
Attention-based graph neural network for molecular solubility prediction
Drug discovery (DD) research is aimed at the discovery of new medications. Solubility is an
important physicochemical property in drug development. Active pharmaceutical ingredients …
important physicochemical property in drug development. Active pharmaceutical ingredients …
Multi-scale context aggregation for strawberry fruit recognition and disease phenotyping
Timely harvesting and disease identification of strawberry fruits is a major concern for
commercial level cultivators. Failing to harvest the grown strawberries can result in the fruit …
commercial level cultivators. Failing to harvest the grown strawberries can result in the fruit …
[HTML][HTML] Identification of piRNA disease associations using deep learning
Piwi-interacting RNAs (piRNAs) play a pivotal role in maintaining genome integrity by
repression of transposable elements, gene stability, and association with various disease …
repression of transposable elements, gene stability, and association with various disease …
iProm-phage: A two-layer model to identify phage promoters and their types using a convolutional neural network
The increased interest in phages as antibacterial agents has resulted in a rise in the number
of sequenced phage genomes, necessitating the development of user-friendly …
of sequenced phage genomes, necessitating the development of user-friendly …
Learning from synthetic InSAR with vision transformers: The case of volcanic unrest detection
NI Bountos, D Michail… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The detection of early signs of volcanic unrest preceding an eruption in the form of ground
deformation in interferometric synthetic aperture radar (InSAR) data is critical for assessing …
deformation in interferometric synthetic aperture radar (InSAR) data is critical for assessing …
SEiPV-Net: An efficient deep learning framework for autonomous multi-defect segmentation in electroluminescence images of solar photovoltaic modules
A robust and efficient segmentation framework is essential for accurately detecting and
classifying various defects in electroluminescence images of solar PV modules. With the …
classifying various defects in electroluminescence images of solar PV modules. With the …
HLNet model and application in crop leaf diseases identification
Y Xu, S Kong, Z Gao, Q Chen, Y Jiao, C Li - Sustainability, 2022 - mdpi.com
Crop disease has been a severe issue for agriculture, causing economic loss for growers.
Thus, disease identification urgently needs to be addressed, especially for precision …
Thus, disease identification urgently needs to be addressed, especially for precision …
Sigma70Pred: A highly accurate method for predicting sigma70 promoter in Escherichia coli K-12 strains
S Patiyal, N Singh, MZ Ali, DS Pundir… - Frontiers in …, 2022 - frontiersin.org
Sigma70 factor plays a crucial role in prokaryotes and regulates the transcription of most of
the housekeeping genes. One of the major challenges is to predict the sigma70 promoter or …
the housekeeping genes. One of the major challenges is to predict the sigma70 promoter or …
[HTML][HTML] Cross-species enhancer prediction using machine learning
Cis-regulatory elements (CREs) are non-coding parts of the genome that play a critical role
in gene expression regulation. Enhancers, as an important example of CREs, interact with …
in gene expression regulation. Enhancers, as an important example of CREs, interact with …