
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 19, 2024
Language: Английский
Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 19, 2024
Language: Английский
Biomolecules, Journal Year: 2024, Volume and Issue: 14(4), P. 409 - 409
Published: March 27, 2024
Proteins need to be located in appropriate spatiotemporal contexts carry out their diverse biological functions. Mislocalized proteins may lead a broad range of diseases, such as cancer and Alzheimer’s disease. Knowing where target protein resides within cell will give insights into tailored drug design for As the gold validation standard, conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, biomarker tags subcellular location identification. However, booming era proteomics high-throughput sequencing generates tons newly discovered proteins, making localization by wet-lab experiments mission impossible. To tackle this concern, past decades, artificial intelligence (AI) machine learning (ML), especially deep methods, have made significant progress research area. In article, we review latest advances AI-based method development three typical types approaches, including sequence-based, knowledge-based, image-based methods. We also elaborately discuss existing challenges future directions field.
Language: Английский
Citations
3Published: March 4, 2024
Proteins need to be located in appropriate spatiotemporal contexts carry out their diverse biological functions. Mislocalized proteins may lead a broad range of diseases, such as cancer and Alzheimer’s disease. Knowing where target protein resides within cell will give insights into tailored drug design for As the gold validation standard, conventional wet lab uses fluorescent microscopy imaging, immunoelectron microscopy, biomarker tags subcellular location identification. However, booming era proteomics high-throughput sequencing generates tons newly discovered proteins, making subcel-lular localization by wet-lab experiments mission impossible. To tackle this concern, past decades, artificial intelligence (AI) machine learning (ML), especially deep methods, have made significant progress research area. In article, we review latest advances AI-based method development three typical types approaches, including sequence-based, knowledge-based, image-based methods. We also elaborately discuss existing challenges future directions field.
Language: Английский
Citations
2International Immunopharmacology, Journal Year: 2024, Volume and Issue: 140, P. 112827 - 112827
Published: Aug. 8, 2024
Language: Английский
Citations
1Ophthalmic Genetics, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 8
Published: Nov. 28, 2024
Introduction Classically, Usher syndrome is characterized by the association of sensorineural hearing loss (SNHL), retinitis pigmentosa (RP) and possible vestibular dysfunction. Pathogenic bi-allelic variants in CEP250 cause atypical autosomal recessive syndrome, which associated with SNHL photoreceptors 20 dysfunction without signs. To date, only 19 scattered descriptions have been reported. In this study, we present detailed clinical genetic description 7 unrelated individuals related disease, along a literature review to provide new insight on severity course disease.
Language: Английский
Citations
1Biochemical Pharmacology, Journal Year: 2024, Volume and Issue: 232, P. 116691 - 116691
Published: Dec. 3, 2024
Language: Английский
Citations
1Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown
Published: June 19, 2024
Language: Английский
Citations
0