The model of proteolysis

This document presents the original approach for estimating parameters of proteolysis process. Data used to fit the model are taken from mass
spectrometric experiments. For parameters estimation the Levenberg-Marquadt algorithm is used. The motivation for model is a hypothesis
that discrimination between cancer patients and healthy donors can be based on activity of peptide cleaving enzymes (i.e. peptidases)

Jaccard/Tanimoto similarity test and estimation methods

Binary data are used in a broad area of biological sciences. Using binary presence-absence data, we can evaluate species co-occurrences that help elucidate relationships among organisms and environments. To summarize similarity between occurrences of species, we routinely use the Jaccard/Tanimoto coefficient, which is the ratio of their intersection to their union. It is natural, then, to identify statistically significant Jaccard/Tanimoto coefficients, which suggest non-random co-occurrences of species. However, statistical hypothesis testing using this similarity coefficient has been seldom used or studied. We introduce a hypothesis test for similarity for biological presence-absence data, using the Jaccard/Tanimoto coefficient. Several key improvements are presented including unbiased estimation of expectation and centered Jaccard/Tanimoto coefficients, that account for occurrence probabilities. We derived the exact and asymptotic solutions and developed the bootstrap and measurement concentration algorithms to compute statistical significance of binary similarity. Comprehensive simulation studies demonstrate that our proposed methods produce accurate p-values and false discovery rates. The proposed estimation methods are orders of magnitude faster than the exact solution. The proposed methods are implemented in an open source R package called jaccard (https://cran.r-project.org/package=jaccard). We introduce a suite of statistical methods for the Jaccard/Tanimoto similarity coefficient, that enable straightforward incorporation of probabilistic measures in analysis for species co-occurrences. Due to their generality, the proposed methods and implementations are applicable to a wide range of binary data arising from genomics, biochemistry, and other areas of science

Contextual Multiple Sequence Alignment

In a recently proposed contextual alignment model, efficient algorithms exist for global and local pairwise alignment of protein sequences. Preliminary results obtained for biological data are very promising. Our main motivation was to adopt the idea of context dependency to the multiple alignment setting. To this aim the relaxation of the model was developed (we call this new model averaged contextual alignment) and a new family of amino acids substitution matrices are constructed. In this paper we present a contextual multiple alignment algorithm and report the outcomes of experiments performed for the BAliBASE test set. The contextual approach turned out to give much better results for the set of sequences containing orphan genes

Diversity and structure of PIF/Harbinger-like elements in the genome of Medicago truncatula

<p>Abstract</p> <p>Background</p> <p>Transposable elements constitute a significant fraction of plant genomes. The <it>PIF/Harbinger </it>superfamily includes DNA transposons (class II elements) carrying terminal inverted repeats and producing a 3 bp target site duplication upon insertion. The presence of an ORF coding for the DDE/DDD transposase, required for transposition, is characteristic for the autonomous <it>PIF/Harbinger</it>-like elements. Based on the above features, <it>PIF/Harbinger</it>-like elements were identified in several plant genomes and divided into several evolutionary lineages. Availability of a significant portion of <it>Medicago truncatula </it>genomic sequence allowed for mining <it>PIF/Harbinger</it>-like elements, starting from a single previously described element <it>MtMaster</it>.</p> <p>Results</p> <p>Twenty two putative autonomous, i.e. carrying an ORF coding for TPase and complete terminal inverted repeats, and 67 non-autonomous <it>PIF/Harbinger</it>-like elements were found in the genome of <it>M. truncatula</it>. They were divided into five families, <it>MtPH-A5</it>, <it>MtPH-A6</it>, <it>MtPH-D</it>,<it>MtPH-E</it>, and <it>MtPH-M</it>, corresponding to three previously identified and two new lineages. The largest families, <it>MtPH-A6 </it>and <it>MtPH-M </it>were further divided into four and three subfamilies, respectively. Non-autonomous elements were usually direct deletion derivatives of the putative autonomous element, however other types of rearrangements, including inversions and nested insertions were also observed. An interesting structural characteristic – the presence of 60 bp tandem repeats – was observed in a group of elements of subfamily <it>MtPH-A6-4</it>. Some families could be related to miniature inverted repeat elements (MITEs). The presence of empty <it>loci </it>(RESites), paralogous to those flanking the identified transposable elements, both autonomous and non-autonomous, as well as the presence of transposon insertion related size polymorphisms, confirmed that some of the mined elements were capable for transposition.</p> <p>Conclusion</p> <p>The population of <it>PIF/Harbinger</it>-like elements in the genome of <it>M. truncatula </it>is diverse. A detailed intra-family comparison of the elements' structure proved that they proliferated in the genome generally following the model of abortive gap repair. However, the presence of tandem repeats facilitated more pronounced rearrangements of the element internal regions. The insertion polymorphism of the <it>MtPH </it>elements and related MITE families in different populations of <it>M. truncatula</it>, if further confirmed experimentally, could be used as a source of molecular markers complementary to other marker systems.</p

Efficient seeding techniques for protein similarity search

We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to construct seeds with optimal sensitivity/selectivity trade-offs. We propose several different design methods and use them to construct several alphabets.We then perform an analysis of seeds built over those alphabet and compare them with the standard Blastp seeding method [2,3], as well as with the family of vector seeds proposed in [4]. While the formalism of subset seed is less expressive (but less costly to implement) than the accumulative principle used in Blastp and vector seeds, our seeds show a similar or even better performance than Blastp on Bernoulli models of proteins compatible with the common BLOSUM62 matrix

Efficient seeding techniques for protein similarity search

We apply the concept of subset seeds proposed in [1] to similarity search in protein sequences. The main question studied is the design of efficient seed alphabets to construct seeds with optimal sensitivity/selectivity trade-offs. We propose several different design methods and use them to construct several alphabets.We then perform an analysis of seeds built over those alphabet and compare them with the standard Blastp seeding method [2,3], as well as with the family of vector seeds proposed in [4]. While the formalism of subset seed is less expressive (but less costly to implement) than the accumulative principle used in Blastp and vector seeds, our seeds show a similar or even better performance than Blastp on Bernoulli models of proteins compatible with the common BLOSUM62 matrix

Tav4SB: integrating tools for analysis of kinetic models of biological systems

BACKGROUND: Progress in the modeling of biological systems strongly relies on the availability of specialized computer-aided tools. To that end, the Taverna Workbench eases integration of software tools for life science research and provides a common workflow-based framework for computational experiments in Biology. RESULTS: The Taverna services for Systems Biology (Tav4SB) project provides a set of new Web service operations, which extend the functionality of the Taverna Workbench in a domain of systems biology. Tav4SB operations allow you to perform numerical simulations or model checking of, respectively, deterministic or stochastic semantics of biological models. On top of this functionality, Tav4SB enables the construction of high-level experiments. As an illustration of possibilities offered by our project we apply the multi-parameter sensitivity analysis. To visualize the results of model analysis a flexible plotting operation is provided as well. Tav4SB operations are executed in a simple grid environment, integrating heterogeneous software such as Mathematica, PRISM and SBML ODE Solver. The user guide, contact information, full documentation of available Web service operations, workflows and other additional resources can be found at the Tav4SB project’s Web page: http://bioputer.mimuw.edu.pl/tav4sb/. CONCLUSIONS: The Tav4SB Web service provides a set of integrated tools in the domain for which Web-based applications are still not as widely available as for other areas of computational biology. Moreover, we extend the dedicated hardware base for computationally expensive task of simulating cellular models. Finally, we promote the standardization of models and experiments as well as accessibility and usability of remote services

Applying dynamic Bayesian networks to perturbed gene expression data

BACKGROUND: A central goal of molecular biology is to understand the regulatory mechanisms of gene transcription and protein synthesis. Because of their solid basis in statistics, allowing to deal with the stochastic aspects of gene expressions and noisy measurements in a natural way, Bayesian networks appear attractive in the field of inferring gene interactions structure from microarray experiments data. However, the basic formalism has some disadvantages, e.g. it is sometimes hard to distinguish between the origin and the target of an interaction. Two kinds of microarray experiments yield data particularly rich in information regarding the direction of interactions: time series and perturbation experiments. In order to correctly handle them, the basic formalism must be modified. For example, dynamic Bayesian networks (DBN) apply to time series microarray data. To our knowledge the DBN technique has not been applied in the context of perturbation experiments. RESULTS: We extend the framework of dynamic Bayesian networks in order to incorporate perturbations. Moreover, an exact algorithm for inferring an optimal network is proposed and a discretization method specialized for time series data from perturbation experiments is introduced. We apply our procedure to realistic simulations data. The results are compared with those obtained by standard DBN learning techniques. Moreover, the advantages of using exact learning algorithm instead of heuristic methods are analyzed. CONCLUSION: We show that the quality of inferred networks dramatically improves when using data from perturbation experiments. We also conclude that the exact algorithm should be used when it is possible, i.e. when considered set of genes is small enough