Simultaneous analysis of two or more samples on the same chromatographic column

Summary Pseudo random binary and ternary sequences (PRBS and PRTS) have already been used to identify impulse responses of linear systems—in particular, we have shown [1,2], how decorrelation techniques allow the chromatogram of a given sample to be obtained by injecting the product following a PRBS or PRTS law. In this paper an additional difficulty is overcome by injecting in parallel two different samples onto one column, then obtaining simultaneously but separately the two chromatograms by use of numerical decorrelation. We present the theoretical justification and the result of numerical simulation in the case of a pseudo random ternary sequence injection law. A successful experiment on an actual chromatograph using a pseudo random binary sequence injection law is presented.     

Phylogenetic inference from binary sequences reduced by primary DNA sequences

Given a bi-classification of nucleotides, we can obtain a reduced binary sequence of a primary DNA sequence. This binary sequence will undoubtedly retain some biological information and lose the rest. Here we want to know what kind of and how much biological information an individual binary sequence carries. Three classifications of nucleotides are explored in the present article. Phylogenetic trees are built from these binary sequences by the Neighbor-Joining (NJ) method, with evolutionary distance evaluated on the basis of a symbolic sequence complexity. We find that, for all data sets studied, binary sequences reduced by the purine/pyrimidine classification give reliable phylogeny (almost the same as that from the primary sequences), while the other two result in discrepancies at different levels. Some possible reasons and a simple model of sequence evolutionary are introduced to interpret this phenomenon.     

Core trees and consensus fragment sequences for molecular representation and similarity analysis

A new type of molecular representation is introduced that is based on activity class characteristic substructures extracted from random fragment populations. Mapping of characteristic substructures is used to determine atom match rates in active molecules. Comparison of match rates of bonded atoms defines a hierarchical molecular fragmentation scheme. Active compounds are encoded as fragmentation pathways isolated from core trees. These paths are amenable to biological sequence alignment methods in combination with substructure-based scoring functions. From multiple core path alignments, consensus fragment sequences are derived that represent compound activity classes. Consensus fragment sequences weighted by increasing structural specificity can also be used to map molecules and search databases for active compounds.     

提高芯片毛细管电泳系统检测信噪比的哈达玛变换法

采用门控进样,在简单的十字通道微流控玻璃芯片上实现了假随机多次进样,研究了利用哈达玛变换提高微流控毛细管电泳分析系统信噪比的方法.在实验中,以7阶127步假随机二进制序列作为进样模板,将缓冲液和Cy₅衍生后的氨基酸试样交替注入到分离通道中,检测到的电泳信号经过哈达玛反变换还原使信噪比提高5倍(理论上5.6倍)的电泳谱,各组分的出峰时间、峰高和峰形均完全还原,毛细管电泳分离的采样频率不受影响.     

Random sequences with power-law correlations exhibit proteinlike behavior

We use a replica approach to investigate the thermodynamic properties of the random heteropolymers with persistent power-law correlations in monomer sequence. We show that this type of sequences possess proteinlike properties. In particular, we show that they can fold into stable unique three-dimensional structure (the "native" structure, in protein terminology) through two different types of pathways. One is a fast folding pathway and leads directly to the native structure. Another one, a more slower pathway, passes through the microphase separated (MPS) state and includes a number of intermediate glassy states. The scale and the magnitude of the MPS are calculated. The frozen state can be reached only by sequences with weak long-range correlations. The critical value for the correlation exponent is found, above which (strong correlations) freezing is impossible.     

Numerical characterization and similarity analysis of DNA sequences based on 2-D graphical representation of the characteristic sequences

Based on the classifications of the four nucleic acid bases, He and Wang reduced a DNA sequence to three binary sequences, which are called the characteristic sequences (J. Chem. Inf. Comput. Sci. 42 (2002) 1080). In this paper, we associate each characteristic sequence with a (b)L / (b)L matrix by giving a 2-D 'two horizontal lines' graphical representation, and thus obtain a 3-component vector with entries being the sums of the maximal and minimal eigenvalues of the (b)L / (b)L matrices. The introduced vector results in more simple characterizations and comparisons among the coding sequences of exon 1 of beta-globin gene of eleven different species.     

Role of foldability and stability in designing real protein sequences

This work explores the effects of two different fitness criteria, the free energy of folding (ΔG(folding)) and foldability (Φ) of mutated sequences, by measuring the designed protein's robustness via cumulative random point mutations. The results of a self-consistent mean-field based theory are used to design 'wild type' protein sequences corresponding to a specified target structure for a given foldability criteria Φ. The theory is applied on three 36-mer real protein conformations and the 'wild type' sequences are identified in terms of site specific monomer probabilities corresponding to a given foldability. Unlike the stability criteria, ΔG(folding) < 0, the foldability criteria Φ(mutated) < -1 effectively identifies sequences of different site-specific monomer identities by specifying the mean and variance of the energy of the unfolded state ensemble. The results depict a distinct difference in the pattern of mutational robustness of the neutral sequence space, Φ(mutated) < -1 scans more number of neutral sequences compared to ΔG(folding) < 0 to find the evolutionary fit sequences. Φ(mutated) < -1 also accounts for marginally stable sequences which are not effectively scanned by ΔG(folding) < 0 to determine evolutionary fitness. The results clearly point out that viable mutated sequences that are foldable, may not always conform to ΔG(fold) < 0, hence assessing the role of foldability in addition to stability for determining protein's robustness towards cumulative random point mutations. These observations may be used in engineering and designing de novo protein sequences which are more robust towards random point mutations.     

Formation,growth mechanism and packing sequences of binary alloy cluster anions from laser ablation of mixtures of lead and transition metals

By using laser ablation of the mixtures of a transition metal (M: Ti, Cr, Mn, Fe, Co, Ni, Cu, Zn, Pd, Ag) plus lead, M/Pb binary cluster anions were observed except for Zn, and the number of transition metal atoms contained in the binary clusters is at most 4. This behavior is different from that reported previously for M/Ge binary clusters. The experiments indicate that it is also very difficult to form Al/Pb clusters. The distribution patterns of M/Pb binary alloy cluster anions are remarkably similar to those of pure Pb clusters, consistent with a formation mechanism in which transition metal atoms are sequentially attached to [M(x-1)Pb(y)](-) clusters and thus form [M(x)Pb(y)](-) clusters by a simple condensation process. As the number of transition metal atoms increases, the intensities of binary clusters gradually decrease. It is proposed that [MPb(4)](-) and [MPb(5)](-) cluster anions might be the unit building blocks of M/Pb binary cluster anions, and the layer packing sequences for magic clusters are predicted on this basis. The [M(x)Pb(y)](-) binary clusters containing 13 atoms (x + y = 13; x not equal 0) are proposed to have an icosahedral structure.     

Characterization of DNA primary sequences based on the average distances between bases.

We outline numerical characterization of DNA primary sequence based on calculation of the average distance between pairs of nucleic acid bases. This leads to a representation of DNA by a condensed 4 x 4 symmetrical matrix, the elements of which give the average separation between pair of bases X, Y in DNA (X, Y = A, C, G, T). As an invariant of choice we consider the leading eigenvalue of the derived 4 x 4 matrix. Additional structurally related invariants were obtained by constructing additional "higher order" 4 x 4 matrices derived from the initial 4 x 4 matrix by raising its elements to higher powers. Suitably normalized leading eigenvalue of these matrices offer a novel characterization of DNA primary sequences, referred to as "DNA profiles". The approach is illustrated on exon 1 of human beta-globin gene.     

Chemical Composition Distribution of Multicomponent Copolymers

The number and weight chemical composition distributions in random terpolymers were derived using a statistical approach. The solution was then generalized to comprise higher multicomponent copolymers. The analytical solution was verified with Monte Carlo simulations and by considering limiting cases. Chemical composition distributions for fractions of random terpolymers of various kinetic chain lengths were also investigated. In a similar way to the results for binary copolymers described by Stockmayer's distribution, broadening of the distribution is observed for low‐molecular‐weight chains.

Comparison of chemical composition distributions from Stockmayer (Equation ( 3 )) and statistical approach (Equation ( 4 )).     

基于伪随机二进制序列的阻抗谱快速重构及其在电化学能源领域的应用

阻抗谱的应用范围越来越广,其传统测试方法耗时长的问题也日益突出. 提高阻抗谱测量速度的各种尝试中,合成宽带激励信号和设计高效率估计算法被认为是最具潜力的解决方案,由于伪随机二进制序列（pseudo-random binary sequence,PRBS）具有功率谱平坦和易生成等优点,它在阻抗谱快速测试中具有独特优势. 本文综述了快速阻抗谱测试中三个核心问题：PRBS信号类型、不同快速算法及其在电化学能源领域的典型应用. 对于PRBS信号类型,即最大长度序列信号、混合PRBS、离散区间二进制序列和正交PRBS,本文讨论了它们各自的特点和应用范围;对于不同的PRBS激励信号的快速算法,即离散傅里叶变换/快速傅里叶变换、小波变换、快速m序列变换、基于系统辨识的参数估计算法以及这些算法各自的特点和应用范围,本文进行了深入的分析;对于PRBS阻抗谱快速测量的应用,本文以铅酸电池、锂离子电池、质子交换膜燃料电池和超级电容器等电化学能源为例,验证了其应用的可行性. 为促进技术的进一步完善,本文总结和分析了PRBS阻抗谱快速测量存在的挑战,并提出了克服这些挑战所必需的未来研究方略.     

Condensed representation of DNA primary sequences

With rapid reporting of DNA sequences derived from automated DNA sequencing techniques, the problem of reviewing and ordering such information has become acute. We have introduced a condensed representation of primary sequences of DNA that offers an alternative method of registering DNA. The advantage of the condensed codes for DNA is that it not only offers fast, qualitative comparisons of DNA but also allows quantitative comparisons of DNA from different sources. The approach is outlined for a particular human beta globin sequence extract. Using the condensed representation of the primary DNA sequences, comparisons are made between primary sequences for Exon 1 of human beta globin and seven other beta globins.     

Discovering protein-binding RNA motifs with a generative model of RNA sequences

Recent advances in high-throughput experimental technologies have generated a huge amount of data on interactions between proteins and nucleic acids. Motivated by the big experimental data, several computational methods have been developed either to predict binding sites in a sequence or to determine if an interaction exists between protein and nucleic acid sequences. However, most of the methods cannot be used to discover new nucleic acid sequences that bind to a target protein because they are classifiers rather than generators. In this paper we propose a generative model for constructing protein-binding RNA sequences and motifs using a long short-term memory (LSTM) neural network. Testing the model for several target proteins showed that RNA sequences generated by the model have high binding affinity and specificity for their target proteins and that the protein-binding motifs derived from the generated RNA sequences are comparable to the motifs from experimentally validated protein-binding RNA sequences. The results are promising and we believe this approach will help design more efficient in vitro or in vivo experiments by suggesting potential RNA aptamers for a target protein.     

"Masterpiece" copolymer sequences by targeted equilibrium-shifting

We describe an equilibrium model to determine whether a random population of dynamic copolymer sequences could be driven by molecular recognition to a subset of sequences that tightly bind a specific ligand. The model predicts that the population's mean binding constant can be shifted, but because of competitive binding, only to a limited degree (ca. 2 orders of magnitude larger than the original mean). True chemical evolution will require a mechanism for selection and amplification.     

Design of amino acid sequences to fold into C(alpha)-model proteins

In order to extend the results obtained with minimal lattice models to more realistic systems, we study a model where proteins are described as a chain of 20 kinds of structureless amino acids moving in a continuum space and interacting through a contact potential controlled by a 20x20 quenched random matrix. The goal of the present work is to design and characterize amino acid sequences folding to the SH3 conformation, a 60-residue recognition domain common to many regulatory proteins. We show that a number of sequences can fold, starting from a random conformation, to within a distance root-mean-square deviation between 2.6 and 4.0 A from the native state. Good folders are those sequences displaying in the native conformation an energy lower than a sequence-independent threshold energy.     

Monomer-scale design of functional protein polymers using consensus repeat sequences

Protein-based polymers possess chemically defined sequences that can encode diverse properties and functions into a new class of biopolymeric materials. However, sequence variation that emerges from evolution can obscure the sequence–function relationships of naturally derived polymers. One strategy to clarify these relationships is to identify common sequences between proteins with similar functions. These conserved sequences often emerge from repeat proteins, and “consensus repeat sequences” provide a convenient platform for systematic investigations of biopolymer sequence–property relationships. In this review, we highlight recent approaches to engineer tunable polymeric materials using monomer-scale design of consensus repeat proteins. We explore established and emerging protein-based materials with mechanical resilience, thermodynamic phase behavior, chemical responsiveness, biomolecular transport, and hierarchical structure. Overall, recent advances in the monomer-scale design of repetitive protein polymers present exciting fundamental and translational opportunities for polymer scientists and engineers.     

LC-mass spectrometry analysis of N- and C-terminal boundary sequences of polypeptide fragments by limited proteolysis

Limited proteolysis is an important and widely used method for analyzing the tertiary structure and determining the domain boundaries of proteins. Here we describe a novel method for determining the N- and C-terminal boundary amino acid sequences of products derived from limited proteolysis using semi-specific and/or non-specific enzymes, with mass spectrometry as the only analytical tool. The core of this method is founded on the recognition that cleavage of proteins with non-specific proteases is not random, but patterned. Based on this recognition, we have the ability to determine the sequence of each proteolytic fragment by extracting a common association between data sets containing multiple potential sequences derived from two or more different mass spectral molecular weight measurements. Proteolytic product sequences derived from specific and non-specific enzymes can be accurately determined without resorting to the conventional time-consuming and laborious methods of SDS-PAGE and N-terminal sequencing analysis. Because of the sensitivity of mass spectrometry, multiple transient proteolysis intermediates can also be identified and analyzed by this method, which allows the ability to monitor the progression of proteolysis and thereby gain insight into protein structures.     

Similarity analysis of DNA sequences based on the generalized LZ complexity of (0,1)-sequences

Based on the permutation of a binary alphabet, four generalized LZ complexities of a (0,1)-sequence are introduced. Since the logical representation of a DNA primary sequence includes four logical sequences, a DNA primary sequence can be characterized by a 16-D vector whose entries are the complexities corresponding to the logical sequences. The utility of the new quantitative characterization of DNA sequences is illustrated by an examination of the similarity among the full β-globin genes of 11 different species.     

Recurrent equations of physicochemical constants for homologs substantiated with numerical sequences

The applicability of the unified first order recurrent equations A(n + 1) = aA(n) + b to the approximation of the physicochemical constants of various organic compounds (not only members of homologous series), previously found for normal boiling points, was extended to the dielectric constant (ε). This tendency is equivalent to the general procedure for calculating the ε of any compound from the data for preceding homologs with an accuracy comparable to the average interlaboratory reproducibility of the results of ε measurements. To substantiate this universal character of recurrent relations we consider the analogy between the constants of successive homologs and the recursive numerical sequences (Fibonacci and Padovan sequences versus Lucas and Perrin sequences, respectively).