Zobrazeno 1 - 10
of 65
pro vyhledávání: '"Somayyeh Koohi"'
Publikováno v:
BMC Genomics, Vol 25, Iss 1, Pp 1-16 (2024)
Abstract Background In recent years, there has been a growing interest in utilizing computational approaches to predict drug-target binding affinity, aiming to expedite the early drug discovery process. To address the limitations of experimental meth
Externí odkaz:
https://doaj.org/article/f5b768117e824680bd3a386b27280c99
Publikováno v:
Journal of Translational Medicine, Vol 21, Iss 1, Pp 1-14 (2023)
Abstract This paper addresses the crucial task of identifying DNA/RNA binding sites, which has implications in drug/vaccine design, protein engineering, and cancer research. Existing methods utilize complex neural network structures, diverse input ty
Externí odkaz:
https://doaj.org/article/c2a1ad5fda9247b881d29487290a5c44
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-18 (2023)
Abstract Background The prevalence of the COVID-19 disease in recent years and its widespread impact on mortality, as well as various aspects of life around the world, has made it important to study this disease and its viral cause. However, very lon
Externí odkaz:
https://doaj.org/article/a06cf5ced16a4b55a83468c8371c07b8
Publikováno v:
BMC Genomics, Vol 24, Iss 1, Pp 1-13 (2023)
Abstract Background It is now possible to analyze cellular heterogeneity at the single-cell level thanks to the rapid developments in single-cell sequencing technologies. The clustering of cells is a fundamental and common step in heterogeneity analy
Externí odkaz:
https://doaj.org/article/4ed769d2554a4200b8d41beda4d5dfe6
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-16 (2023)
Abstract The Major Histocompatibility Complex (MHC) binds to the derived peptides from pathogens to present them to killer T cells on the cell surface. Developing computational methods for accurate, fast, and explainable peptide-MHC binding predictio
Externí odkaz:
https://doaj.org/article/11d06f84c1ac4155b14c0acf6b2e1463
Publikováno v:
PLoS ONE, Vol 19, Iss 8, p e0307279 (2024)
Features extraction methods, such as k-mer-based methods, have recently made up a significant role in classifying and analyzing approaches for metagenomics data. But, they are challenged by various bottlenecks, such as performance limitations, high m
Externí odkaz:
https://doaj.org/article/77856d9142dd4afba4699d2bb1a33356
Autor:
Hoda Sadeghzadeh, Somayyeh Koohi
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-17 (2022)
Abstract The classification performance of all-optical Convolutional Neural Networks (CNNs) is greatly influenced by components’ misalignment and translation of input images in the practical applications. In this paper, we propose a free-space all-
Externí odkaz:
https://doaj.org/article/3fb9056b06fe4df98064b2ba3199c0b7
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-25 (2022)
Abstract Bio-sequence comparators are one of the most basic and significant methods for assessing biological data, and so, due to the importance of proteins, protein sequence comparators are particularly crucial. On the other hand, the complexity of
Externí odkaz:
https://doaj.org/article/138d6fa0647142a9b37fb5cd8badad86
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 3, p e1011036 (2023)
Drug-target binding affinity prediction plays a key role in the early stage of drug discovery. Numerous experimental and data-driven approaches have been developed for predicting drug-target binding affinity. However, experimental methods highly rely
Externí odkaz:
https://doaj.org/article/53facca664284d0297ff10f8d57e48e3
Autor:
Hoda Sadeghzadeh, Somayyeh Koohi
Publikováno v:
IEEE Photonics Journal, Vol 14, Iss 4, Pp 1-12 (2022)
Convolutional neural networks (CNNs) are at the heart of several machine learning applications, while they suffer from computational complexity due to their large number of parameters and operations. Recently, all-optical implementation of the CNNs h
Externí odkaz:
https://doaj.org/article/00b105d46cda4d9aa0687aa22244e233