The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational biology.One of the most cutting-edge and important applications of ML is its integration with...The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational biology.One of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large biomolecules.This review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational landscape.We first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy landscape.Further,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein conformations.Lastly,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann weights.Collectively,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.展开更多
Structurally compact battery packs significantly improve the driving range of electric vehicles.Technologies like Cell-to-Pack increase energy density by 15%-20%.However,the safety implications of multiple tightly-pac...Structurally compact battery packs significantly improve the driving range of electric vehicles.Technologies like Cell-to-Pack increase energy density by 15%-20%.However,the safety implications of multiple tightly-packed battery cells still require in-depth research.This paper studies thermal runaway propagation behavior in a Cell-to-Pack system and assesses propagation speed relative to other systems.The investigation includes temperature response,extent of battery damage,pack structure deformation,chemical analysis of debris,and other considerations.Results suggest three typical patterns for the thermal runaway propagation process:ordered,disordered,and synchronous.The synchronous propagation pattern displayed the most severe damage,indicating energy release is the largest under the synchronous pattern.This study identifies battery deformation patterns,chemical characteristics of debris,and other observed factors that can both be applied to identify the cause of thermal runaway during accident investigations and help promote safer designs of large battery packs used in large-scale electric energy storage systems.展开更多
In this study, PCR-RFLP technique was employed to detect the genetic polymorphism of NPY gene and analyze the effects of various genotypes on the total number of eggs at 300 days of age in 135 Donglan black-bone chick...In this study, PCR-RFLP technique was employed to detect the genetic polymorphism of NPY gene and analyze the effects of various genotypes on the total number of eggs at 300 days of age in 135 Donglan black-bone chicken. According to the results, there were three genotypes （AA, AB and BB） of NPYgene in Donglan black-bone chicken group. Different genotypes exhibited significant effects （P 〈 0. 05 ） on the total number of eggs at 300 days of age. The total number of eggs at 300 days of age of AA genotype was significantly higher than that of BB genotype （P 〈 0. 05）. Therefore, the polymorphic site of NPY gene could be used as a candidate molecular marker that affects egg laying in Donglan black-bone chicken.展开更多
To assess the indica-japonica differentiation of improved rice varieties, a total of 512 modem varieties including 301 indica and 211 japonica accessions were analyzed using 36 microsatellites. The Fst coefficients ra...To assess the indica-japonica differentiation of improved rice varieties, a total of 512 modem varieties including 301 indica and 211 japonica accessions were analyzed using 36 microsatellites. The Fst coefficients ranged from 0.002 to 0.730 among the loci with an average of 0.315. Significant differentiation was detected at 94.4% of the loci studied （P 〈 0.05, pairwise Fst tests）, indicating that there was a high level of indica-japonica differentiation within the improved varieties. At 18 loci, about 74%-98% of the alleles of indica and japonica accessions were distributed in two ranges of amplicon length. Linkage disequilibrium analysis showed that the distribution trends were significantly nonrandomly associated. Using the differentiation trends at the 18 loci, microsatellite index （MI） was proposed for discrimination of the two subspecies. When rice accessions with MI value greater than zero were classified as indica, and those with MI value smaller than zero were classified as japonica, about 96.1% of the accessions could be classified. This result agrees with the classification based on morphological-physiological characters, indicating that this method is feasible and effective.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant No.2023YFF1204402)the National Natural Science Foundation of China(Grant Nos.12074079 and 12374208)+1 种基金the Natural Science Foundation of Shanghai(Grant No.22ZR1406800)the China Postdoctoral Science Foundation(Grant No.2022M720815).
文摘The rapid advancement and broad application of machine learning(ML)have driven a groundbreaking revolution in computational biology.One of the most cutting-edge and important applications of ML is its integration with molecular simulations to improve the sampling efficiency of the vast conformational space of large biomolecules.This review focuses on recent studies that utilize ML-based techniques in the exploration of protein conformational landscape.We first highlight the recent development of ML-aided enhanced sampling methods,including heuristic algorithms and neural networks that are designed to refine the selection of reaction coordinates for the construction of bias potential,or facilitate the exploration of the unsampled region of the energy landscape.Further,we review the development of autoencoder based methods that combine molecular simulations and deep learning to expand the search for protein conformations.Lastly,we discuss the cutting-edge methodologies for the one-shot generation of protein conformations with precise Boltzmann weights.Collectively,this review demonstrates the promising potential of machine learning in revolutionizing our insight into the complex conformational ensembles of proteins.
基金supported by the Natural Science Foundation of Hebei Province (B2021507001)the National Natural Science Foundation of China (52106284, 52076121)+2 种基金the Ministry of Science and Technology (2022YFE0207900)the support of the Science and Technology Project of Langfang (2021011017)the Project to Promote Innovation in Doctoral Research at CPPU (BSKY202302)。
文摘Structurally compact battery packs significantly improve the driving range of electric vehicles.Technologies like Cell-to-Pack increase energy density by 15%-20%.However,the safety implications of multiple tightly-packed battery cells still require in-depth research.This paper studies thermal runaway propagation behavior in a Cell-to-Pack system and assesses propagation speed relative to other systems.The investigation includes temperature response,extent of battery damage,pack structure deformation,chemical analysis of debris,and other considerations.Results suggest three typical patterns for the thermal runaway propagation process:ordered,disordered,and synchronous.The synchronous propagation pattern displayed the most severe damage,indicating energy release is the largest under the synchronous pattern.This study identifies battery deformation patterns,chemical characteristics of debris,and other observed factors that can both be applied to identify the cause of thermal runaway during accident investigations and help promote safer designs of large battery packs used in large-scale electric energy storage systems.
基金Supported by Natural Science Foundation of Guangxi Zhuang Autonomous Region(2013jj DA30049)
文摘In this study, PCR-RFLP technique was employed to detect the genetic polymorphism of NPY gene and analyze the effects of various genotypes on the total number of eggs at 300 days of age in 135 Donglan black-bone chicken. According to the results, there were three genotypes （AA, AB and BB） of NPYgene in Donglan black-bone chicken group. Different genotypes exhibited significant effects （P 〈 0. 05 ） on the total number of eggs at 300 days of age. The total number of eggs at 300 days of age of AA genotype was significantly higher than that of BB genotype （P 〈 0. 05）. Therefore, the polymorphic site of NPY gene could be used as a candidate molecular marker that affects egg laying in Donglan black-bone chicken.
基金supported by the National Basic Research Program of China (No.2004CB117201)National Natural Science Foundation of China (No.30600388)the Key Technologies Research and Development Program of China (No.2006BAD13B01)
文摘To assess the indica-japonica differentiation of improved rice varieties, a total of 512 modem varieties including 301 indica and 211 japonica accessions were analyzed using 36 microsatellites. The Fst coefficients ranged from 0.002 to 0.730 among the loci with an average of 0.315. Significant differentiation was detected at 94.4% of the loci studied （P 〈 0.05, pairwise Fst tests）, indicating that there was a high level of indica-japonica differentiation within the improved varieties. At 18 loci, about 74%-98% of the alleles of indica and japonica accessions were distributed in two ranges of amplicon length. Linkage disequilibrium analysis showed that the distribution trends were significantly nonrandomly associated. Using the differentiation trends at the 18 loci, microsatellite index （MI） was proposed for discrimination of the two subspecies. When rice accessions with MI value greater than zero were classified as indica, and those with MI value smaller than zero were classified as japonica, about 96.1% of the accessions could be classified. This result agrees with the classification based on morphological-physiological characters, indicating that this method is feasible and effective.
