2,041 research outputs found

    RNA secondary structure formation: a solvable model of heteropolymer folding

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    The statistical mechanics of heteropolymer structure formation is studied in the context of RNA secondary structures. A designed RNA sequence biased energetically towards a particular native structure (a hairpin) is used to study the transition between the native and molten phase of the RNA as a function of temperature. The transition is driven by a competition between the energy gained from the polymer's overlap with the native structure and the entropic gain of forming random contacts. A simplified Go-like model is proposed and solved exactly. The predicted critical behavior is verified via exact numerical enumeration of a large ensemble of similarly designed sequences.Comment: 4 pages including 2 figure

    Thermodynamics of protein folding: a random matrix formulation

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    The process of protein folding from an unfolded state to a biologically active, folded conformation is governed by many parameters e.g the sequence of amino acids, intermolecular interactions, the solvent, temperature and chaperon molecules. Our study, based on random matrix modeling of the interactions, shows however that the evolution of the statistical measures e.g Gibbs free energy, heat capacity, entropy is single parametric. The information can explain the selection of specific folding pathways from an infinite number of possible ways as well as other folding characteristics observed in computer simulation studies.Comment: 21 Pages, no figure

    Counting, generating and sampling tree alignments

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    Pairwise ordered tree alignment are combinatorial objects that appear in RNA secondary structure comparison. However, the usual representation of tree alignments as supertrees is ambiguous, i.e. two distinct supertrees may induce identical sets of matches between identical pairs of trees. This ambiguity is uninformative, and detrimental to any probabilistic analysis.In this work, we consider tree alignments up to equivalence. Our first result is a precise asymptotic enumeration of tree alignments, obtained from a context-free grammar by mean of basic analytic combinatorics. Our second result focuses on alignments between two given ordered trees SS and TT. By refining our grammar to align specific trees, we obtain a decomposition scheme for the space of alignments, and use it to design an efficient dynamic programming algorithm for sampling alignments under the Gibbs-Boltzmann probability distribution. This generalizes existing tree alignment algorithms, and opens the door for a probabilistic analysis of the space of suboptimal RNA secondary structures alignments.Comment: ALCOB - 3rd International Conference on Algorithms for Computational Biology - 2016, Jun 2016, Trujillo, Spain. 201

    Cancer: leaping the E‐cadherin hurdle

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    Aberrant activation of the Wnt signaling pathway is a common cause of colon cancer and other tumor types, accomplishing many of the hallmarks of cancer including sustained proliferative signaling, replicative immortality, reprogrammed metabolism, angiogenesis, and invasion. Yet, the dominant mutation that leads to chronic Wnt signaling in colon cancer is quite different from the spectrum of mutations that activate Wnt signaling in other tumor types. In this issue of The EMBO Journal, Huels et al (2015) focus on the influential role E-cadherin plays in shaping these differences

    Addition-Deletion Networks

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    We study structural properties of growing networks where both addition and deletion of nodes are possible. Our model network evolves via two independent processes. With rate r, a node is added to the system and this node links to a randomly selected existing node. With rate 1, a randomly selected node is deleted, and its parent node inherits the links of its immediate descendants. We show that the in-component size distribution decays algebraically, c_k ~ k^{-beta}, as k-->infty. The exponent beta=2+1/(r-1) varies continuously with the addition rate r. Structural properties of the network including the height distribution, the diameter of the network, the average distance between two nodes, and the fraction of dangling nodes are also obtained analytically. Interestingly, the deletion process leads to a giant hub, a single node with a macroscopic degree whereas all other nodes have a microscopic degree.Comment: 8 pages, 5 figure

    Rank Statistics in Biological Evolution

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    We present a statistical analysis of biological evolution processes. Specifically, we study the stochastic replication-mutation-death model where the population of a species may grow or shrink by birth or death, respectively, and additionally, mutations lead to the creation of new species. We rank the various species by the chronological order by which they originate. The average population N_k of the kth species decays algebraically with rank, N_k ~ M^{mu} k^{-mu}, where M is the average total population. The characteristic exponent mu=(alpha-gamma)/(alpha+beta-gamma)$ depends on alpha, beta, and gamma, the replication, mutation, and death rates. Furthermore, the average population P_k of all descendants of the kth species has a universal algebraic behavior, P_k ~ M/k.Comment: 4 pages, 3 figure

    Predictive value of Altmetric score on citation rates and bibliometric impact

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    Background Bibliometric and Altmetric analyses provide different perspectives regarding research impact. This study aimed to determine whether Altmetric score was associated with citation rate independent of established bibliometrics. Methods Citations related to a previous cohort of 100 most cited articles in surgery were collected and a 3-year interval citation gain calculated. Citation count, citation rate index, Altmetric score, 5-year impact factor, and Oxford Centre for Evidence-Based Medicine levels were used to estimate citation rate prospect. Results The median interval citation gain was 161 (i.q.r. 83–281); 74 and 62 articles had an increase in citation rate index (median increase 2.8 (i.q.r. –0.1 to 7.7)) and Altmetric score (median increase 3 (0–4)) respectively. Receiver operating characteristic (ROC) curve analysis revealed that citation rate index (area under the curve (AUC) 0.86, 95 per cent c.i. 0.79 to 0.93; P < 0.001) and Altmetric score (AUC 0.65, 0.55 to 0.76; P = 0.008) were associated with higher interval citation gain. An Altmetric score critical threshold of 2 or more was associated with a better interval citation gain when dichotomized at the interval citation gain median (odds ratio (OR) 4.94, 95 per cent c.i. 1.99 to 12.26; P = 0.001) or upper quartile (OR 4.13, 1.60 to 10.66; P = 0.003). Multivariable analysis revealed only citation rate index to be independently associated with interval citation gain when dichotomized at the median (OR 18.22, 6.70 to 49.55; P < 0.001) or upper quartile (OR 19.30, 4.23 to 88.15; P < 0.001). Conclusion Citation rate index and Altmetric score appear to be important predictors of interval citation gain, and better at predicting future citations than the historical and established impact factor and Oxford Centre for Evidence-Based Medicine quality descriptors

    Fr-TM-align: a new protein structural alignment method based on fragment alignments and the TM-score

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    ©2008 Pandit and Skolnick; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is available from: http://www.biomedcentral.com/1471-2105/9/531doi:10.1186/1471-2105-9-531Background: Protein tertiary structure comparisons are employed in various fields of contemporary structural biology. Most structure comparison methods involve generation of an initial seed alignment, which is extended and/or refined to provide the best structural superposition between a pair of protein structures as assessed by a structure comparison metric. One such metric, the TM-score, was recently introduced to provide a combined structure quality measure of the coordinate root mean square deviation between a pair of structures and coverage. Using the TM-score, the TM-align structure alignment algorithm was developed that was often found to have better accuracy and coverage than the most commonly used structural alignment programs; however, there were a number of situations when this was not true. Results: To further improve structure alignment quality, the Fr-TM-align algorithm has been developed where aligned fragment pairs are used to generate the initial seed alignments that are then refined using dynamic programming to maximize the TM-score. For the assessment of the structural alignment quality from Fr-TM-align in comparison to other programs such as CE and TMalign, we examined various alignment quality assessment scores such as PSI and TM-score. The assessment showed that the structural alignment quality from Fr-TM-align is better in comparison to both CE and TM-align. On average, the structural alignments generated using Fr-TM-align have a higher TM-score (~9%) and coverage (~7%) in comparison to those generated by TM-align. Fr- TM-align uses an exhaustive procedure to generate initial seed alignments. Hence, the algorithm is computationally more expensive than TM-align. Conclusion: Fr-TM-align, a new algorithm that employs fragment alignment and assembly provides better structural alignments in comparison to TM-align. The source code and executables of Fr- TM-align are freely downloadable at: http://cssb.biology.gatech.edu/skolnick/files/FrTMalign/

    A simple, practical and complete O-time Algorithm for RNA folding using the Four-Russians Speedup

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    <p>Abstract</p> <p>Background</p> <p>The problem of computationally predicting the secondary structure (or folding) of RNA molecules was first introduced more than thirty years ago and yet continues to be an area of active research and development. The basic <it>RNA-folding problem </it>of finding a maximum cardinality, non-crossing, matching of complimentary nucleotides in an RNA sequence of length <it>n</it>, has an <it>O</it>(<it>n</it><sup>3</sup>)-time dynamic programming solution that is widely applied. It is known that an <it>o</it>(<it>n</it><sup>3</sup>) worst-case time solution is possible, but the published and suggested methods are complex and have not been established to be practical. Significant practical improvements to the original dynamic programming method have been introduced, but they retain the <it>O</it>(<it>n</it><sup>3</sup>) worst-case time bound when <it>n </it>is the only problem-parameter used in the bound. Surprisingly, the most widely-used, general technique to achieve a worst-case (and often practical) speed up of dynamic programming, the <it>Four-Russians </it>technique, has not been previously applied to the RNA-folding problem. This is perhaps due to technical issues in adapting the technique to RNA-folding.</p> <p>Results</p> <p>In this paper, we give a simple, complete, and practical Four-Russians algorithm for the basic RNA-folding problem, achieving a worst-case time-bound of <it>O</it>(<it>n</it><sup>3</sup>/log(<it>n</it>)).</p> <p>Conclusions</p> <p>We show that this time-bound can also be obtained for richer nucleotide matching scoring-schemes, and that the method achieves consistent speed-ups in practice. The contribution is both theoretical and practical, since the basic RNA-folding problem is often solved multiple times in the inner-loop of more complex algorithms, and for long RNA molecules in the study of RNA virus genomes.</p

    Using XML and XSLT for flexible elicitation of mental-health risk knowledge

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    Current tools for assessing risks associated with mental-health problems require assessors to make high-level judgements based on clinical experience. This paper describes how new technologies can enhance qualitative research methods to identify lower-level cues underlying these judgements, which can be collected by people without a specialist mental-health background. Methods and evolving results: Content analysis of interviews with 46 multidisciplinary mental-health experts exposed the cues and their interrelationships, which were represented by a mind map using software that stores maps as XML. All 46 mind maps were integrated into a single XML knowledge structure and analysed by a Lisp program to generate quantitative information about the numbers of experts associated with each part of it. The knowledge was refined by the experts, using software developed in Flash to record their collective views within the XML itself. These views specified how the XML should be transformed by XSLT, a technology for rendering XML, which resulted in a validated hierarchical knowledge structure associating patient cues with risks. Conclusions: Changing knowledge elicitation requirements were accommodated by flexible transformations of XML data using XSLT, which also facilitated generation of multiple data-gathering tools suiting different assessment circumstances and levels of mental-health knowledge
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