分类: 信息科学与系统科学 >> 信息科学与系统科学基础学科 分类: 生物学 >> 生物进化论 分类: 生物学 >> 生物数学 分类: 物理学 >> 交叉学科物理及相关领域的科学与技术 分类: 生物学 >> 遗传学 提交时间: 2023-10-15
摘要: Background: In bioinformatics, tools like multiple sequence alignment and entropy methods probe sequence information and evolutionary relationships between species. Although powerful, they might miss crucial hierarchical relationships formed by the reuse of repetitive subsequences like duplicons and transposable elements. Such relationships are governed by evolutionary tinkering'', as described by Fran c{c}ois Jacob. The newly developed Ladderpath theory provides a quantitative framework to describe these hierarchical relationships.Results: Based on this theory, we introduce two indicators: order-rate $ eta$, characterizing sequence pattern repetitions and regularities, and ladderpath-complexity $ kappa$, characterizing hierarchical richness within sequences, considering sequence length. Statistical analyses on real amino acid sequences showed: (1) Among the typical species analyzed, humans possess relatively more sequences with large $ kappa$ values. (2) Proteins with a significant proportion of intrinsically disordered regions exhibit increased $ eta$ values. (3) There are almost no super long sequences with low $ eta$. We hypothesize that this arises from varied duplication and mutation frequencies across different evolutionary stages, which in turn suggests a zigzag pattern for the evolution of protein complexity. This is supported by our simulations and examples from protein families such as Ubiquitin and NBPF.Conclusions: Our method emphasizes how objects are generated'', capturing the essence of evolutionary tinkering and reuse. The findings hint at a connection between sequence orderliness and structural uncertainty, and suggest that different species or those in varied environments might adopt distinct protein elongation strategies. These insights highlight our method's value for further in-depth evolutionary biology applications.
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: Context. Stellar coronal mass ejections (CMEs) are the primary driver of the exoplanetary space weather and they could affect the habitability of exoplanets. However, detections of possible stellar CME signatures are extremely rare. Aims. This work aims to detect stellar CMEs from time-domain spectra observed through the LAMOST Medium-Resolution Spectroscopic Survey (LAMOST-MRS). Our sample includes 1,379,408 LAMOST-MRS spectra of 226,194 late-type main-sequence stars ($\rm T_{eff} 4.0$). Methods. We first identified stellar CME candidates by examining the asymmetries of H$\alpha$ line profiles, and then performed double Gaussian fitting for H$\alpha$ contrast profiles (differences between the CME spectra and reference spectra) of the CME candidates to analyze the temporal variation of the asymmetric components. Results. Three stellar CME candidates were detected on three M dwarfs. The H$\alpha$ and Mg I triplet lines (at 5168.94 {\AA}, 5174.13 {\AA}, 5185.10 {\AA}) of candidate 1 all exhibit a blue-wing enhancement, and the corresponding Doppler shift of this enhancement shows a gradually increasing trend. The H$\alpha$ line also shows an obvious blue-wing enhancement in candidate 2. In candidate 3, the H$\alpha$ line shows an obvious red-wing enhancement, and the corresponding projected maximum velocity exceeds the surface escape velocity of the host star. The lower limit of the CME mass was estimated to be $\sim$$8 \times 10^{17}$ g to $4 \times 10^{18}$ g for these three candidates.
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch in December 2020, GECAM-B has detected hundreds of astronomical and terrestrial events. For these bursts, localization is the key for burst identification and classification as well as follow-up observations in multi-wavelength. Here, we propose a Bayesian localization method with Poisson data with Gaussian background profile likelihood to localize GECAM bursts based on the burst counts distribution in detectors with different orientations. We demonstrate that this method can work well for all kinds of bursts, especially for extremely short ones. In addition, we propose a new method to estimate the systematic error of localization based on a confidence level test, which can overcome some problems of the existing method in literature. We validate this method by Monte Carlo simulations, and then apply it to a burst sample with accurate location and find that the mean value of the systematic error of GECAM-B localization is $\sim 2.5^{\circ}$. By considering this systematic error, we can obtain a reliable localization probability map for GECAM bursts. Our methods can be applied to other gamma-ray monitors.
分类: 天文学 >> 天文学 提交时间: 2023-02-19
摘要: Gravitational wave high-energy Electromagnetic Counterpart All-sky Monitor (GECAM) is a pair of microsatellites (i.e. GECAM-A and GECAM-B) dedicated to monitoring gamma-ray transients including gravitational waves high-energy electromagnetic counterparts, Gamma-ray Bursts, Soft Gamma-ray Repeaters, Solar Flares and Terrestrial Gamma-ray Flashes. Since launch in December 2020, GECAM-B has detected hundreds of astronomical and terrestrial events. For these bursts, localization is the key for burst identification and classification as well as follow-up observations in multi-wavelength. Here, we propose a Bayesian localization method with Poisson data with Gaussian background profile likelihood to localize GECAM bursts based on the burst counts distribution in detectors with different orientations. We demonstrate that this method can work well for all kinds of bursts, especially for extremely short ones. In addition, we propose a new method to estimate the systematic error of localization based on a confidence level test, which can overcome some problems of the existing method in literature. We validate this method by Monte Carlo simulations, and then apply it to a burst sample with accurate location and find that the mean value of the systematic error of GECAM-B localization is $\sim 2.5^{\circ}$. By considering this systematic error, we can obtain a reliable localization probability map for GECAM bursts. Our methods can be applied to other gamma-ray monitors.