A hybrid method for identification of structural domains

Hua, Yongpan; Zhu, Min; Wang, Yuelong; Xie, ZhaoYang; Li, Menglong

doi:10.1038/srep07476

Cited by 2 publications

(2 citation statements)

References 25 publications

(41 reference statements)

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“…OAM beams have been investigated for numerous applications in classical and quantum fields, including particle trapping and rotating, [1,2] microscopic imaging, [3,4] optical communication, [5,6] high-dimensional quantum entanglement [7] and quantum key distribution. [8,9] Traditionally, OAM beams DOI: 10.1002/lpor.202300837 have been generated using spatial light modulator, [10,11] cylindrical lens pair, [12] spiral phase plate, [13] Q-plate, [14] fiberbased devices, [15] metasurfaces [16] and photonic integrated devices. [17] Recently, several free space-based schemes have been reported to tailor the OAM spectrum or generate an OAM comb.…”

Section: Introductionmentioning

confidence: 99%

Coherent Optical Comb Generation in the Joint Space of Frequency and Topological Charge

Li,

Zeng,

Xie

et al. 2024

Laser & Photonics Reviews

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Coherent photonic states in the frequency domain or optical frequency combs are investigated widely over the past decade. Meanwhile, photonic states based on spatial coherence, in particular optical vortex states, have also been studied extensively. Further exploitation of coherent photonics state in hitherto unexplored higher dimensional spaces can reveal new realms of physics. The on‐chip generation of coherent optical combs in the 2D parameter space of frequency and topological charge is reported. Using a micro‐ring resonator embedded with angular gratings, optical frequency combs are generated by Kerr nonlinearity. The coherent comb lines, with their frequencies inherently matching the cavity resonances, are immediately diffracted by the angular grating to emit an ensemble of coherent spatial photonic states with each state carrying distinctive spin and orbital angular momenta. The mapping between the frequency and the topological charge dimensions leads to the construction of coherent combs in the high‐dimensional frequency‐topological charge (f‐l) space. Operating the device in the normal‐dispersion regime enables the adjustment of comb line spacing from 1 to 11 free spectral ranges by selectively pumping different cavity resonances with high pump‐to‐comb conversion efficiency. Such on‐chip reconfigurable high‐dimensional coherent optical combs open avenues for innovative exploration of physics.

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Section: Introductionmentioning

confidence: 99%

Coherent Optical Comb Generation in the Joint Space of Frequency and Topological Charge

Li,

Zeng,

Xie

et al. 2024

Laser & Photonics Reviews

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“…SWORD [43] is one of the latest automated methods that addressed this problem by offering alternative decompositions for a protein chain, though producing multiple parsing is not unprecedented among the previous methods [44,45]. Nevertheless, presenting new algorithmic methods of protein decomposition is desirable since each approach bears certain disadvantages [46] and complex structures are often required to be tackled with different strategies for a convenient partitioning.…”

Section: Introductionmentioning

confidence: 99%

Assignment of structural domains in proteins using diffusion kernels on graphs

et al. 2022

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Though proposing algorithmic approaches for protein domain decomposition has been of high interest, the inherent ambiguity to the problem makes it still an active area of research. Besides, accurate automated methods are in high demand as the number of solved structures for complex proteins is on the rise. While majority of the previous efforts for decomposition of 3D structures are centered on the developing clustering algorithms, employing enhanced measures of proximity between the amino acids has remained rather uncharted. If there exists a kernel function that in its reproducing kernel Hilbert space, structural domains of proteins become well separated, then protein structures can be parsed into domains without the need to use a complex clustering algorithm. Inspired by this idea, we developed a protein domain decomposition method based on diffusion kernels on protein graphs. We examined all combinations of four graph node kernels and two clustering algorithms to investigate their capability to decompose protein structures. The proposed method is tested on five of the most commonly used benchmark datasets for protein domain assignment plus a comprehensive non-redundant dataset. The results show a competitive performance of the method utilizing one of the diffusion kernels compared to four of the best automatic methods. Our method is also able to offer alternative partitionings for the same structure which is in line with the subjective definition of protein domain. With a competitive accuracy and balanced performance for the simple and complex structures despite relying on a relatively naive criterion to choose optimal decomposition, the proposed method revealed that diffusion kernels on graphs in particular, and kernel functions in general are promising measures to facilitate parsing proteins into domains and performing different structural analysis on proteins. The size and interconnectedness of the protein graphs make them promising targets for diffusion kernels as measures of affinity between amino acids. The versatility of our method allows the implementation of future kernels with higher performance. The source code of the proposed method is accessible at https://github.com/taherimo/kludo. Also, the proposed method is available as a web application from https://cbph.ir/tools/kludo.

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A hybrid method for identification of structural domains

Cited by 2 publications

References 25 publications

Coherent Optical Comb Generation in the Joint Space of Frequency and Topological Charge

Coherent Optical Comb Generation in the Joint Space of Frequency and Topological Charge

Assignment of structural domains in proteins using diffusion kernels on graphs

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