PanDelos: a dictionary-based method for pan-genome content discovery.

BACKGROUND: Pan-genome approaches afford the discovery of homology relations in a set of genomes, by determining how some gene families are distributed among a given set of genomes. The retrieval of a complete gene distribution among a class of genomes is an NP-hard problem because computational costs increase with the number of analyzed genomes, in fact, all-against-all gene comparisons are required to completely solve the problem. In presence of phylogenetically distant genomes, due to the variability introduced in gene duplication and transmission, the task of recognizing homologous genes becomes even more difficult. A challenge on this field is that of designing fast and adaptive similarity measures in order to find a suitable pan-genome structure of homology relations. RESULTS: We present PanDelos, a stand alone tool for the discovery of pan-genome contents among phylogenetic distant genomes. The methodology is based on information theory and network analysis. It is parameter-free because thresholds are automatically deduced from the context. PanDelos avoids sequence alignment by introducing a measure based on k-mer multiplicity. The k-mer length is defined according to general arguments rather than empirical considerations. Homology candidate relations are integrated into a global network and groups of homologous genes are extracted by applying a community detection algorithm. CONCLUSIONS: PanDelos outperforms existing approaches, Roary and EDGAR, in terms of running times and quality content discovery. Tests were run on collections of real genomes, previously used in analogous studies, and in synthetic benchmarks that represent fully trusted golden truth. The software is available at https://github.com/GiugnoLab/PanDelos .

An Informational Test for Random Finite Strings.

In this paper, by extending some results of informational genomics, we present a new randomness test based on the empirical entropy of strings and some properties of the repeatability and unrepeatability of substrings of certain lengths. We give the theoretical motivations of our method and some experimental results of its application to a wide class of strings: decimal representations of real numbers, roulette outcomes, logistic maps, linear congruential generators, quantum measurements, natural language texts, and genomes. It will be evident that the evaluation of randomness resulting from our tests does not distinguish among the different sources of randomness (natural, or pseudo-casual).

Informational laws of genome structures.

In recent years, the analysis of genomes by means of strings of length k occurring in the genomes, called k-mers, has provided important insights into the basic mechanisms and design principles of genome structures. In the present study, we focus on the proper choice of the value of k for applying information theoretic concepts that express intrinsic aspects of genomes. The value k = lg2(n), where n is the genome length, is determined to be the best choice in the definition of some genomic informational indexes that are studied and computed for seventy genomes. These indexes, which are based on information entropies and on suitable comparisons with random genomes, suggest five informational laws, to which all of the considered genomes obey. Moreover, an informational genome complexity measure is proposed, which is a generalized logistic map that balances entropic and anti-entropic components of genomes and is related to their evolutionary dynamics. Finally, applications to computational synthetic biology are briefly outlined.

MP-GeneticSynth: inferring biological network regulations from time series.

MP-GeneticSynth is a Java tool for discovering the logic and regulation mechanisms responsible for observed biological dynamics in terms of finite difference recurrent equations. The software makes use of: (i) metabolic P systems as a modeling framework, (ii) an evolutionary approach to discover flux regulation functions as linear combinations of given primitive functions, (iii) a suitable reformulation of the least squares method to estimate function parameters considering simultaneously all the reactions involved in complex dynamics. The tool is available as a plugin for the virtual laboratory MetaPlab. It has graphical and interactive interfaces for data preparation, a priori knowledge integration, and flux regulator analysis. Availability and implementation: Source code, binaries, documentation (including quick start guide and videos) and case studies are freely available at http://mplab.sci.univr.it/plugins/mpgs/index.html.

MpTheory Java library: a multi-platform Java library for systems biology based on the Metabolic P theory.

UNLABELLED: MpTheory Java library is an open-source project collecting a set of objects and algorithms for modeling observed dynamics by means of the Metabolic P (MP) theory, that is, a mathematical theory introduced in 2004 for modeling biological dynamics. By means of the library, it is possible to model biological systems both at continuous and at discrete time. Moreover, the library comprises a set of regression algorithms for inferring MP models starting from time series of observations. To enhance the modeling experience, beside a pure Java usage, the library can be directly used within the most popular computing environments, such as MATLAB, GNU Octave, Mathematica and R. AVAILABILITY AND IMPLEMENTATION: The library is open-source and licensed under the GNU Lesser General Public License (LGPL) Version 3.0. Source code, binaries and complete documentation are available at http://mptheory.scienze.univr.it. CONTACT: luca.marchetti@univr.it, marchetti@cosbi.eu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Modeling time-dependent transcription effects of HER2 oncogene and discovery of a role for E2F2 in breast cancer cell-matrix adhesion.

MOTIVATION: Oncogenes are known drivers of cancer phenotypes and targets of molecular therapies; however, the complex and diverse signaling mechanisms regulated by oncogenes and potential routes to targeted therapy resistance remain to be fully understood. To this end, we present an approach to infer regulatory mechanisms downstream of the HER2 driver oncogene in SUM-225 metastatic breast cancer cells from dynamic gene expression patterns using a succession of analytical techniques, including a novel MP grammars method to mathematically model putative regulatory interactions among sets of clustered genes. RESULTS: Our method highlighted regulatory interactions previously identified in the cell line and a novel finding that the HER2 oncogene, as opposed to the proto-oncogene, upregulates expression of the E2F2 transcription factor. By targeted gene knockdown we show the significance of this, demonstrating that cancer cell-matrix adhesion and outgrowth were markedly inhibited when E2F2 levels were reduced. Thus, validating in this context that upregulation of E2F2 represents a key intermediate event in a HER2 oncogene-directed gene expression-based signaling circuit. This work demonstrates how predictive modeling of longitudinal gene expression data combined with multiple systems-level analyses can be used to accurately predict downstream signaling pathways. Here, our integrated method was applied to reveal insights as to how the HER2 oncogene drives a specific cancer cell phenotype, but it is adaptable to investigate other oncogenes and model systems. AVAILABILITY AND IMPLEMENTATION: Accessibility of various tools is listed in methods; the Log-Gain Stoichiometric Stepwise algorithm is accessible at http://www.cbmc.it/software/Software.php.

From time series to biological network regulations: an evolutionary approach.

In this paper we present a new methodology, based on genetic algorithms and multiple linear regression, for discovering regulation mechanisms responsible for observed time series in biological networks. The modeling framework employed is called Metabolic P systems; they are deterministic and time-discrete dynamical systems proposed as an effective alternative to ordinary differential equations for modeling biochemical systems. Our methodology is here successfully applied to the mitotic oscillator in early amphibian embryos. Starting from the time series of substances involved in this system, we are able to reconstruct an MP system reproducing the observed dynamics, where the regulatory components were discovered by our evolutionary methodology. In particular, genetic algorithms are used as a variable selection technique to identify the best representation of any regulation function in terms of some given primitive functions.

A dictionary based informational genome analysis.

BACKGROUND: In the post-genomic era several methods of computational genomics are emerging to understand how the whole information is structured within genomes. Literature of last five years accounts for several alignment-free methods, arisen as alternative metrics for dissimilarity of biological sequences. Among the others, recent approaches are based on empirical frequencies of DNA k-mers in whole genomes. RESULTS: Any set of words (factors) occurring in a genome provides a genomic dictionary. About sixty genomes were analyzed by means of informational indexes based on genomic dictionaries, where a systemic view replaces a local sequence analysis. A software prototype applying a methodology here outlined carried out some computations on genomic data. We computed informational indexes, built the genomic dictionaries with different sizes, along with frequency distributions. The software performed three main tasks: computation of informational indexes, storage of these in a database, index analysis and visualization. The validation was done by investigating genomes of various organisms. A systematic analysis of genomic repeats of several lengths, which is of vivid interest in biology (for example to compute excessively represented functional sequences, such as promoters), was discussed, and suggested a method to define synthetic genetic networks. CONCLUSIONS: We introduced a methodology based on dictionaries, and an efficient motif-finding software application for comparative genomics. This approach could be extended along many investigation lines, namely exported in other contexts of computational genomics, as a basis for discrimination of genomic pathologies.

Computing by polymerase chain reaction.

A mathematical notation is introduced to represent, at a symbolic level, different mechanisms of DNA recombination, and a 'PCR lemma' is proven by analytically describing the combinatorial properties of the polymerase chain reaction process. This approach led to the discovery of novel techniques, based on a form of PCR which we called cross pairing PCR (briefly XPCR). They were mathematically analyzed and already experimentally proven in different contexts, such as DNA extraction and recombination. Thus, a mathematical analysis of standard methodologies may highlight novel mechanisms of DNA recombination and this can provide new technologies for DNA manipulation.

Biological networks in metabolic P systems.

The metabolic P algorithm is a procedure which determines, in a biochemically realistic way, the evolution of P systems representing biological phenomena. A new formulation of this algorithm is given and a graphical formalism is introduced which seems to be very natural in expressing biological networks by means of a two level representation: a basic biochemical level and a second one which regulates the dynamical interaction among the reactions of the first level. After some basic examples, the mitotic oscillator in amphibian embryos is considered as an important case study. Three formulations of this biological network are developed. The first two are directly derived by Goldbeter's differential equations representation. The last one, entirely deduced by translating the biological description of the phenomenon in our diagrams, exhibits an analogous pattern, but it is conceptually simpler and avoids many details on the kinetic aspects of the reactions.

Dynamical aspects of P systems.

A dynamical analysis of P systems is given that is focused on basic phenomena of biological relevance. After a short presentation of a new kind of P systems (PB systems), membrane systems with environment, called PBE systems, are introduced that are more suitable for modeling complex membrane interactions. Some types of periodicity and non-periodicity are considered for PBE systems by showing some "minimal" examples of systems that exhibit these properties. In particular, a discrete formulation of the Belousov-Zhabotinsky (BZ) reaction is given in terms of PBE systems. Some questions and open problems for future research are indicated.