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Bioinformatics (Oxford, England)
Jun 3, 2024
SUMMARY: The increasing development of sequence-based machine learning models has raised the demand for manipulating sequences for this application. However, existing approaches to edit and evaluate genome sequences using models have limitations, suc...
Bioinformatics (Oxford, England)
May 2, 2024
MOTIVATION: Experimental characterization of fitness landscapes, which map genotypes onto fitness, is important for both evolutionary biology and protein engineering. It faces a fundamental obstacle in the astronomical number of genotypes whose fitne...
Bioinformatics (Oxford, England)
May 2, 2024
MOTIVATION: Protein domains are fundamental units of protein structure and play a pivotal role in understanding folding, function, evolution, and design. The advent of accurate structure prediction techniques has resulted in an influx of new structur...
Bioinformatics (Oxford, England)
May 2, 2024
MOTIVATION: Molecular property prediction (MPP) is a fundamental but challenging task in the computer-aided drug discovery process. More and more recent works employ different graph-based models for MPP, which have achieved considerable progress in i...
Bioinformatics (Oxford, England)
May 2, 2024
MOTIVATION: Despite the extensive manufacturing of antiviral drugs and vaccination, viral infections continue to be a major human ailment. Antiviral peptides (AVPs) have emerged as potential candidates in the pursuit of novel antiviral drugs. These p...
Bioinformatics (Oxford, England)
Mar 29, 2024
MOTIVATION: Personalized cancer treatments require accurate drug response predictions. Existing deep learning methods show promise but higher accuracy is needed to serve the purpose of precision medicine. The prediction accuracy can be improved with ...
Bioinformatics (Oxford, England)
Mar 29, 2024
MOTIVATION: Deep-learning models are transforming biological research, including many bioinformatics and comparative genomics algorithms, such as sequence alignments, phylogenetic tree inference, and automatic classification of protein functions. Amo...
Bioinformatics (Oxford, England)
Mar 29, 2024
MOTIVATION: Genome sequencing technologies reveal a huge amount of genomic sequences. Neural network-based methods can be prime candidates for retrieving insights from these sequences because of their applicability to large and diverse datasets. Howe...
Bioinformatics (Oxford, England)
Mar 29, 2024
MOTIVATION: Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the compl...
Bioinformatics (Oxford, England)
Mar 29, 2024
SUMMARY: Segmentation of neural somata is a crucial and usually the most time-consuming step in the analysis of optical functional imaging of neuronal microcircuits. In recent years, multiple auto-segmentation tools have been developed to improve the...