Pse-in-One 2.0: An Improved Package of Web Servers for Generating Various Modes of Pseudo Components of DNA, RNA, and Protein Sequences

Pse-in-One 2.0 is a package of web-servers evolved from Pse-in-One (Liu, B., Liu, F., Wang, X., Chen, J. Fang, L. & Chou, K.C. Nucleic Acids Research, 2015, 43:W65-W71). In order to make it more flexible and comprehensive as suggested by many users, the updated package has incorporated 23 new pseudo component modes as well as a series of new feature analysis approaches. It is available at http://bioinformatics.hitsz.edu.cn/Pse-in-One2.0/. Moreover, to maximize the convenience of users, provided is also the stand-alone version called “Pse-in-One-Analysis”, by which users can significantly speed up the analysis of massive sequences.

Pseudo-Random Sequences Generator Based on Discrete Hyperchaotic Systems

We first design a discrete hyperchaotic system via piece-wise linear state feedback. The states of the closed loop system are locally expanding in two directions but absolutely bounded on the whole, which implies hyperchaos. Then, we use three suchlike hyperchaotic systems with different feedback gain matrices to design a pseudo-random sequence generator (PRSG). Through a threshold function, three sub-sequences generated from the output of piecewise linear functions are changed into 0-1 sequences. Then, followed by XOR operation, an unpredictable pseudo-random sequence (PRS) is ultimately obtained. The analysis and simulation results indicate that the PRS, generated with hyperchaotic systems, has desirable statistical features.

Pseudo DNA Sequence Generation of Non-Coding Distributions Using Variant Maps on Cellular Automata

In a recent decade, many DNA sequencing projects are developed on cells, plants and animals over the world into huge DNA databases. Researchers notice that mammalian genomes encoding thousands of large noncoding RNAs (lncRNAs), interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. It is a challenge target using higher dimensional tools to organize various complex interactive properties as visual maps. In this paper, a Pseudo DNA Variant MapPDVM is proposed following Cellular Automata to represent multiple maps that use four Meta symbols as well as DNA or RNA representations. The system architecture of key components and the core mechanism on the PDVM are described. Key modules, equations and their I/O parameters are discussed. Applying the PDVM, two sets of real DNA sequences from both the sample human (noncoding DNA) and corn (coding DNA) genomes are collected in comparison with two sets of pseudo DNA sequences generated by a stream cipher HC-256 under different modes to show their intrinsic properties in higher levels of similar relationships among relevant DNA sequences on 2D maps. Sample 2D maps are listed and their characteristics are illustrated under a controllable environment. Various distributions can be observed on both noncoding and coding conditions from their symmetric properties on 2D maps.

HIERACHICAL STRUCTURES FOR GENERATING PSEUDO-RANDOM SEQUENCES AND ARRAYS

This paper proposes new hierarchical structures for generating pseudorandom sequences and arrays. The principle of the structures is based on a new concept-multi-interleaving. It is the generalization of normal sequence decimation(sampling). The kernal of the structures is a lower speed linear feedback shift register together with several high speed time-division multiplexers arranged hierarchically. These new structures have much higher speed compared with that of other schemes proposed before.

SOME CONVERGENCE PROBLEM OF ITERATIVE SEQUENCESFOR ACCRETIVE AND PSEUDO-CONTRACTIVETYPE MAPPING IN BANACH SPACES

Some necessary and sufficient conditions for convergence of Ishikawa Mann and steepest descent iterative sequence for accretive and pseudo-contractive type mapping in Banach spaces were obtained. The results improve, extend and include some recent results.

Non-Supervised Learning for Spread Spectrum Signal Pseudo-Noise Sequence Acquisition

An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.

Prediction of the Earlier Strong Aftershocks in the Earthquake Sequences by the Pseudo-Periodicity Method

We propose the pseudo-periodicity method and its quantitative prediction indexes for the occurrence time of earlier strong aftershock. We conducted tests of regressive prediction, and the R-value of the tests is 0.45, indicating that this method is effective for prediction.

Variant Map System to Simulate Complex Properties of DNA Interactions Using Binary Sequences

Stream cipher, DNA cryptography and DNA analysis are the most important R&D fields in both Cryptography and Bioinformatics. HC-256 is an emerged scheme as the new generation of stream ciphers for advanced network security. From a random sequencing viewpoint, both sequences of HC-256 and real DNA data may have intrinsic pseudo-random properties respectively. In a recent decade, many DNA sequencing projects are developed on cells, plants and animals over the world into huge DNA databases. Researchers notice that mammalian genomes encode thousands of large noncoding RNAs (lncRNAs), interact with chromatin regulatory complexes, and are thought to play a role in localizing these complexes to target loci across the genome. It is a challenge target using higher dimensional visualization tools to organize various complex interactive properties as visual maps. The Variant Map System (VMS) as an emerging scheme is systematically proposed in this paper to apply multiple maps that used four Meta symbols as same as DNA or RNA representations. System architecture of key components and core mechanism on the VMS are described. Key modules, equations and their I/O parameters are discussed. Applying the VM System, two sets of real DNA sequences from both sample human (noncoding DNA) and corn (coding DNA) genomes are collected in comparison with pseudo DNA sequences generated by HC-256 to show their intrinsic properties in higher levels of similar relationships among relevant DNA sequences on 2D maps. Sample 2D maps are listed and their characteristics are illustrated under controllable environment. Visual results are briefly analyzed to explore their intrinsic properties on selected genome sequences.

Approach to blind estimation of the PN sequence in DS-SS signals with residual carrier

This paper presents an approach of singular value de- composition plus digital phase lock loop to solve the difficult problem of blind pseudo-noise （PN） sequence estimation in low signal to noise ratios （SNR） direct sequence spread spectrum （DS-SS） signals with residual carrier. This approach needs some given parameters, such as the period and code rate of PN sequence. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. An autocorrelation matrix is then computed and accumulated by those signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of the autocorrelation matrix. Further more, a digital phase lock loop is used to process the estimated PN sequence, it estimates and tracks the residual carrier and removes the residual carrier in the end. Theory analysis and computer simulation results show that this approach can effectively realize the PN sequence blind estimation from the input DS-SS signals with residual carrier in lower SNR.

The Hyperspace of the Regions Below of Continuous Maps from the Converging Sequence

Let S = {1,1/2,1/2^2,…,1/∞ = 0} and I = [0, 1] be the unit interval. We use ↓USC（S） and ↓C（S） to denote the families of the regions below of all upper semi-continuous maps and of the regions below of all continuous maps from S to I and ↓C0（S） = {↓f∈↓C（S） ： f（0） = 0}. ↓USC（S） endowed with the Vietoris topology is a topological space. A pair of topological spaces （X, Y） means that X is a topological space and Y is its subspace. Two pairs of topological spaces （X, Y） and （A, B） are called pair-homeomorphic （≈） if there exists a homeomorphism h ： X→A from X onto A such that h（Y） = B. It is proved that, （↓USC（S）,↓C0（S）） ≈（Q, s） and （↓USC（S）,↓C（S）／ ↓C0（S））≈（Q, c0）, where Q = [-1,1]^ω is the Hilbert cube and s = （-1,1）^ω,c0= {（xn）∈Q ： limn→∞= 0}. But we do not know what （↓USC（S）,↓C（S））is.

Autocorrelation of Sequences Generated by Single Cycle T-Functions

Cryptographic properties of the single cycle T-function's output sequences are investigated.Bounds of autocorrelation functions of the kth coordinate sequence and bounds of state output sequence are calculated respectively.The Maximum Sidelobe Ratio(MSR) of the kth coordinate sequence and the MSR of state output sequence are given respectively.The bounds of autocorrelation functions show that the values of autocorrelation functions are large when shifts are small.Comparisons of the autocorrelations between the state output sequence and coordinate output sequence are illustrated.The autocorrelation properties demonstrate that T-functions have cryptographic weaknesses and the illustration result shows coordinate output sequences have better autocorrelation than that of state output sequences.

Binary Sequences from a Pair of Elliptic Curves

A family of binary sequences were constructed by using an elliptic curve and its twisted curves over finite fields. It was shown that these sequences possess ＂good＂ cryptographie properties of 0-1 distribution, long period and large linear complexity. The results indicate that such se quences provide strong potential applications in cryptography.

Multi-Value Sequence Generated over Sub Extension Field and Its Properties

Pseudo-random sequences with long period, low correlation, high linear complexity, and uniform distribution of bit patterns are widely used in the field of information security and cryptography. This paper proposes an approach for generating a pseudo-random multi-value sequence (including a binary sequence) by utilizing a primitive polynomial, trace function, and k-th power residue symbol over the sub extension field. All our previous sequences are defined over the prime field, whereas, proposed sequence in this paper is defined over the sub extension field. Thus, it’s a new and innovative perception to consider the sub extension field during the sequence generation procedure. By considering the sub extension field, two notable outcomes are: proposed sequence holds higher linear complexity and more uniform distribution of bit patterns compared to our previous work which defined over the prime field. Additionally, other important properties of the proposed multi-value sequence such as period, autocorrelation, and cross-correlation are theoretically shown along with some experimental results.

胶质母细胞瘤恶性进展中不同细胞亚群的动态轨迹和细胞通讯网络

目的:探索胶质母细胞瘤(glioblastoma,GBM)恶性进展过程中细胞亚群的动态轨迹以及免疫细胞亚群之间的通讯网络,结合GBM患者的转录组数据和临床信息,挖掘GBM恶性进展过程中的关键风险标志物,以期为该疾病的治疗和预后提供科学依据。方法:基于单细胞测序数据分析方法,构建GBM恶性进展中的细胞亚群图谱,利用Monocle2技术构建GBM恶性进展中肿瘤细胞亚群的动态进展轨迹,基于基因富集分析,挖掘肿瘤细胞亚群随GBM恶性进展中显著变化的基因所富集的生物学过程,利用CellChat软件识别不同免疫细胞亚群间的复杂通讯网络,通过生存分析识别GBM恶性进展中影响患者预后的关键风险分子标记物。结果:单细胞测序数据分析识别出6种不同的细胞类型,包括淋巴细胞、周细胞、少突神经胶质细胞、巨噬细胞、胶质瘤细胞、小胶质细胞,单细胞数据集中了27151个细胞,其中包含3881个来源于低级别胶质瘤患者的细胞,10166个来源于新诊断GBM患者的细胞,13104个来源于复发性胶质瘤患者的细胞。胶质瘤细胞亚群逆时序分析提示,胶质瘤细胞亚群在恶性进展中存在着明显的细胞异质性;免疫细胞亚群的细胞相互作用分析揭示,GBM恶性进展中不同免疫细胞亚群之间的通讯网络共识别出22条具有生物学意义的配体-受体对,涉及12条通路;生存分析识别出8个与GBM患者预后密切相关的基因,其中SERPINE1、COL6A1、SPP1、LTF、C1S、AEBP1、SAA1L是GBM患者的高风险基因,ABCC8是GBM患者的低风险基因。结论:深入揭示了GBM恶性进展中胶质瘤细胞亚群的动态变化以及免疫细胞亚群之间的通讯模式,对于理解GBM的复杂生物学过程具有重要意义,为GBM的精准医疗和治疗决策提供了科学依据,也为GBM患者更准确的预后评估提供了新的线索。

烟草NtPRR37基因克隆及功能分析

【目的】伪答应基因家族(pseudo response regulators,PRRs)是高等植物调控开花途径的重要基因。克隆烟草NtPRR37基因并分析其对不同光周期的应答及对开花的影响,为烟草开花调控提供靶标基因。【方法】利用同源克隆方法从普通烟草(Nicotiana tabacum L.)中克隆得到NtPRR37基因,并对其进行生物信息学分析,利用实时荧光定量PCR(real-time quantitative PCR,RT-qPCR)分析其在不同组织中的表达及不同光照时长处理的表达模式。同时利用病毒诱导基因沉默(virus induced gene silence,VIGS)技术降低NtPRR37表达水平并观察表型变化及检测开花相关基因表达变化。【结果】NtPRR37基因全长2472 bp,编码823个氨基酸,相对分子质量90.16 kD,含有PRRs基因家族的典型保守结构域(REC和CCT结构域)。通过同源进化分析发现,烟草NtPRR37与绒毛烟草(Nicotiana tomentosiformis)、林烟草(Nicotiana sylvestris)及本氏烟草(Nicotiana benthamiana)的PRR37在进化上属于同一分支。采用RT-qPCR分析发现,该基因在盛花期烟草各个组织的表达特征存在差异性,在雌蕊中的表达量最高,在侧根的表达量最低;在不同光照时长处理下,NtPRR37随着光照时间的增加表达量呈上升趋势,全黑暗处理下表达量最低,且具有生物节律性;NtPRR37沉默植株中NtPRR37表达量明显下调且沉默植株开花期提前,这可能与诱导开花相关基因(NtFT4、NtAP1、NtCO、NtSOC1)表达量显著上调有关。【结论】NtPRR37的表达受到光周期的调控,且在烟草开花过程中NtPRR37作为开花抑制因子存在。

垂直水声通信中的伪随机序列精确定时算法

针对垂直水声通信中时变多普勒引起的定时偏差问题,研究一种基于伪随机序列的迭代定时估计及补偿算法。该方法利用伪随机序列作为同步信号,分三步估计时变多普勒:采用低复杂度的模糊函数法粗补偿接收信号内的平均多普勒;通过迭代插值法实现残留时变多普勒的精确估计及补偿;利用基于信道相关函数的相位信息,纠正均衡后信号的偏转相位。为实现高阶海试数据的有效解调,采用基于伪随机序列均方误差的多通道加权合并方式,获得空间分集增益。仿真及海试数据处理结果证明所提方法具有良好的时变多普勒估计及补偿性能,同时对30个通道内的1024QAM数据进行合并处理,在500 m的通信距离下,误码率为0.04,信道容量达到7.6 bits/symbol。与传统数据帧结构相比,无需使用线性调频信号,可以提高有效数据传输率。

超短基线在低频基阵指向性测量中的应用

随着水声换能器工作频率的降低,实验室空间很难达到自由场和远场测量的要求。而开阔水域的水下环境复杂,基阵很难实现更深层次的吊放,需要安装价格昂贵的吊装平台来获取标准声源与待测基阵之间的相对位姿,效率低且维护成本高。文章采用超短基线定位技术,信号选用线性调频脉冲信号与伪随机编码脉冲信号,并分别基于脉冲压缩法和复相关算法实现距离和相位测量。比对湖上定位精度试验和基阵指向性标定静态试验的结果显示:角度误差为2.5°以内;-6 dB波束宽度在2~10 kHz频率范围内测量误差在5.38%以内。证明超短基线定位在低频基阵指向性标定的可行性。

基于伪随机序列的松散煤体声学测温方法及应用

长期以来,采空区、煤堆、煤仓等空间的煤自燃火灾时有发生,受限于工作区域的复杂环境和火源探测技术瓶颈等因素,较难实现煤自燃灾害高温点的快速量化识别。而声学测温技术具有测量精度高、测温范围宽、测量空间大等特点,可实现采空区等隐蔽火源位置精准探测且极具发展前景。目前该技术在松散煤体温度测量领域尚处于基础研究和实验室研究阶段,仍需开展大量研究。基于伪随机序列的优越性能,将其引入作为声源信号,并根据声学测温原理和伪随机序列声源信号产生原理,搭建了松散煤体声波测温试验系统。系统主体部分包括声学测试系统、程序升温系统、隔音系统和煤样箱体,结合试验测试和仿真模拟方法,验证了系统的准确性。利用理论分析、Matlab仿真和试验测试相结合的方法,开展伪随机序列声源信号的失真特性研究,确定了该信号的最佳处理方法,成功将其应用于松散煤体测温中。结果表明:伪随机序列可以作为采空区、煤堆、煤仓等空间的松散煤体声学测温的声源信号,但需运用二次相关PHAT–β算法对伪随机序列声源信号发生频率区间(1000~3000 Hz)进行处理,使频带变窄,能量集中;运用伪随机序列声源信号测量声波在松散煤体中飞渡时间,发现不同距离下声波飞渡时间测量结果误差小于5%,并通过了对比验证;伪随机序列作为松散煤体的测温声源信号时,所反演温度与不同粒径的煤样温度之间的平均绝对误差为2.051℃,平均误差率5.293%,能够较为精准、可靠地反演煤温。

考虑加载次序影响的沥青非线性疲劳损伤累积研究

变幅加载下沥青的疲劳损伤累积具有明显的非线性特征,传统的Miner’s线性疲劳损伤累积准则无法表征不同变幅加载次序下沥青的非线性疲劳损伤累积(NLFDA)。该研究旨在建立考虑加载次序影响的NLFDA模型,准确表征加载次序对沥青疲劳损伤累积的影响。通过开展应力控制的沥青恒幅加载疲劳试验,采用耗散伪应变能(DPSE)表征沥青疲劳损伤,分析恒幅加载下沥青的疲劳损伤累积规律;采用低-高和高-低两种加载次序,开展应力控制的沥青变幅加载疲劳试验,分析变幅加载下沥青的疲劳损伤累积规律;基于损伤等效准则,建立考虑加载次序影响的NLFDA模型,分析加载次序对疲劳损伤累积的影响。结果表明:应力控制模式下的沥青疲劳损伤,呈先缓慢后急剧的非线性增加演化趋势;恒幅加载下沥青疲劳损伤服从Miner’s准则发生线性累积,且累积寿命分数等于1;变幅加载下沥青疲劳损伤不服从Miner’s准则而发生非线性累积。低-高和高-低变幅加载次序下,沥青累积疲劳寿命随一级寿命分数的增大而分别增加和减小,累积寿命分数分别大于1和小于1;建立的NLFDA模型可克服Miner’s准则缺陷,并较为准确地表征加载次序对沥青疲劳损伤累积的影响。

DVB-T中伪随机序列扰码器的FPGA实现

伪随机序列在伪码测距、导航、数字数据扰乱器、噪声产生器、通信加密中有着广泛的应用。在这些实际应用中,常常利用现场可编程门阵列(FPGA)来产生伪随机序列,这便于系统设计和测试的实现。针对数字地面电视广播(DVB-T)标准,以线性反馈移位寄存器电路为基础,设计了一种并行伪随机序列产生方法,该方法简单而高效地实现DVB-T系统码流数据的扰码。实验结果表明,MATLAB扰码算法结果与FPGA扰码模块仿真结果和硬件实现结果一致,该设计方法切实可行。