Modelling epistasis in genetic disease using Petri nets, evolutionary computation and frequent itemset mining

Petri nets are useful for mathematically modelling disease-causing genetic epistasis. A Petri net model of an interaction has the potential to lead to biological insight into the cause of a genetic disease. However, defining a Petri net by hand for a particular interaction is extremely difficult because of the sheer complexity of the problem and degrees of freedom inherent in a Petri net’s architecture. We propose therefore a novel method, based on evolutionary computation and data mining, for automatically constructing Petri net models of non-linear gene interactions. The method comprises two main steps. Firstly, an initial partial Petri net is set up with several repeated sub-nets that model individual genes and a set of constraints, comprising relevant common sense and biological knowledge, is also defined. These constraints characterise the class of Petri nets that are desired. Secondly, this initial Petri net structure and the constraints are used as the input to a genetic algorithm. The genetic algorithm searches for a Petri net architecture that is both a superset of the initial net, and also conforms to all of the given constraints. The genetic algorithm evaluation function that we employ gives equal weighting to both the accuracy of the net and also its parsimony. We demonstrate our method using an epistatic model related to the presence of digital ulcers in systemic sclerosis patients that was recently reported in the literature. Our results show that although individual “perfect” Petri nets can frequently be discovered for this interaction, the true value of this approach lies in generating many different perfect nets, and applying data mining techniques to them in order to elucidate common and statistically significant patterns of interaction

Molecular evidence that phoronids are a subtaxon of brachiopods (Brachiopoda: Phoronata) and that genetic divergence of metazoan phyla began long before the early Cambrian

Concatenated SSU (18S) and partial LSU (28S) sequences (~2 kb) from 12 ingroup taxa, comprising 2 phoronids, 2 members of each of the craniid, discinid, and lingulid inarticulate brachiopod lineages, and 4 rhynchonellate, articulate brachiopods (2 rhynchonellides, 1 terebratulide and 1 terebratellide) were aligned with homologous sequences from 6 protostome, deuterostome and sponge outgroups (3964 sites). Regions of potentially ambiguous alignment were removed, and the resulting data (3275 sites, of which 377 were parsimony-informative and 635 variable) were analysed by parsimony, and by maximum and Bayesian likelihood using objectively selected models. There was no base composition heterogeneity. Relative rate tests led to the exclusion (from most analyses) of the more distant outgroups, with retention of the closer pectinid and polyplacophoran (chiton). Parsimony and likelihood bootstrap and Bayesian clade support values were generally high, but only likelihood analyses recovered all brachiopod indicator clades designated a priori. All analyses confirmed the monophyly of (brachiopods+phoronids) and identified phoronids as the sister-group of the three inarticulate brachiopod lineages. Consequently, a revised Linnean classification is proposed in which the subphylum Linguliformea comprises three classes: Lingulata, ‘Phoronata’ (the phoronids), and ‘Craniata’ (the current subphylum Craniiformea). Divergence times of all nodes were estimated by regression from node depths in non-parametrically rate-smoothed and other chronograms, calibrated against palaeontological data, with probable errors not less than 50 My. Only three predicted brachiopod divergence times disagree with palaeontological ages by more than the probable error, and a reasonable explanation exists for at least two. Pruning long-branched ingroups made scant difference to predicted divergence time estimates. The palaeontological age calibration and the existence of Lower Cambrian fossils of both main brachiopod clades together indicate that initial genetic divergence between brachiopod and molluscan (chiton) lineages occurred well before the Lower Cambrian, suggesting that much divergence between metazoan phyla took place in the Proterozoic

Genetic and morphological evidence reveals the existence of a new family, genus and species of Echinorhynchida (Acanthocephala)

Gymnorhadinorhynchus gen. n. is proposed to accommodate its type species, G. decapteri sp. n., a parasite of the marine fish Decapterus punctatus (Cuvier), caught from the coastal waters of Brazil. Gymnorhadinorhynchus decapteri sp. n. was morphologically most similar to species of two echinorhynchid families, the Rhadinorhynchidae and the Cavisomidae, particularly in the structure of the proboscis and the absence of somatic spines, respectively. This combination of morphological features made it difficult to assign our specimen to an extant family of the Acanthocephala. Therefore, in order to clarify the systematic placement of G. decapteri, a molecular phylogenetic analysis was performed based on the SSU and LSU rDNA and the mitochondrial cox1 gene sequences obtained for the new taxon and other 26 acanthocephalan species. The results of parsimony and maximum likelihood analyses, using individual, combined and concatenated sequence data, consistently indicate that the specimens do not belong to any known family of the Echinorhynchida. Rather, G. decapteri represents a distinct lineage that is closely related to the Transvenidae, but distantly related to both the Rhadinorhynchidae and the Cavisomidae. Gymnorhadinorhynchidae fam. n. is therefore erected. This newly described family can be distinguished from other families of Echinorhynchida by the combination of the following morphological characters: a proboscis cylindrical with 10 rows of 22?26 hooks, dorsoventral differences in proboscis hooks, basal hooks forming a ring and being abruptly larger than anterior hooks, absence of trunk spines and presence of four tubular cement glands. This combination, in addition to several molecular autapomorphies, justifies the erection of a new genus, Gymnorhadinorhynchus gen. n., in order to accommodate this new species.Fil: Braicovich, Paola Elizabeth. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Lanfranchi, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; ArgentinaFil: Farber, Marisa Diana. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Marvaldi, Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Provincia de Mendoza. Instituto Argentino de Investigaciones de las Zonas Áridas. Universidad Nacional de Cuyo. Instituto Argentino de Investigaciones de las Zonas Áridas; ArgentinaFil: Luque, José L.. Universidade Federal Rural Do Rio de Janeiro; BrasilFil: Timi, Juan Tomas. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones Marinas y Costeras. Universidad Nacional de Mar del Plata. Facultad de Ciencia Exactas y Naturales. Instituto de Investigaciones Marinas y Costeras; Argentin

Occurrence of Eimeria species parasites on small-scale commercial chicken farms in Africa and indication of economic profitability.

Small-scale commercial poultry production is emerging as an important form of livestock production in Africa, providing sources of income and animal protein to many poor households, yet the occurrence and impact of coccidiosis on this relatively new production system remains unknown. The primary objective of this study was to examine Eimeria parasite occurrence on small-scale commercial poultry farms in Ghana, Tanzania and Zambia. Additionally, farm economic viability was measured by calculating the farm gross margin and enterprise budget. Using these economic measures as global assessments of farm productivity, encompassing the diversity present in regional husbandry systems with a measure of fundamental local relevance, we investigated the detection of specific Eimeria species as indicators of farm profitability. Faecal samples and data on production parameters were collected from small-scale (less than 2,000 birds per batch) intensive broiler and layer farms in peri-urban Ghana, Tanzania and Zambia. All seven Eimeria species recognised to infect the chicken were detected in each country. Furthermore, two of the three genetic variants (operational taxonomic units) identified previously in Australia have been described outside of Australia for the first time. Detection of the most pathogenic Eimeria species associated with decreased farm profitability and may be considered as an indicator of likely farm performance. While a causal link remains to be demonstrated, the presence of highly pathogenic enteric parasites may pose a threat to profitable, sustainable small-scale poultry enterprises in Africa

Machine learning and its applications in reliability analysis systems

In this thesis, we are interested in exploring some aspects of Machine Learning (ML) and its application in the Reliability Analysis systems (RAs). We begin by investigating some ML paradigms and their- techniques, go on to discuss the possible applications of ML in improving RAs performance, and lastly give guidelines of the architecture of learning RAs. Our survey of ML covers both levels of Neural Network learning and Symbolic learning. In symbolic process learning, five types of learning and their applications are discussed: rote learning, learning from instruction, learning from analogy, learning from examples, and learning from observation and discovery. The Reliability Analysis systems (RAs) presented in this thesis are mainly designed for maintaining plant safety supported by two functions: risk analysis function, i.e., failure mode effect analysis (FMEA) ; and diagnosis function, i.e., real-time fault location (RTFL). Three approaches have been discussed in creating the RAs. According to the result of our survey, we suggest currently the best design of RAs is to embed model-based RAs, i.e., MORA (as software) in a neural network based computer system (as hardware). However, there are still some improvement which can be made through the applications of Machine Learning. By implanting the 'learning element', the MORA will become learning MORA (La MORA) system, a learning Reliability Analysis system with the power of automatic knowledge acquisition and inconsistency checking, and more. To conclude our thesis, we propose an architecture of La MORA

Testing use of mitochondrial COI sequences for the identification and phylogenetic analysis of New Zealand caddisflies (Trichoptera)

We tested the hypothesis that cytochrome c oxidase subunit 1 (COI) sequences would successfully discriminate recognised species of New Zealand caddisflies. We further examined whether phylogenetic analyses, based on the COI locus, could recover currently recognised superfamilies and suborders. COI sequences were obtained from 105 individuals representing 61 species and all 16 families of Trichoptera known from New Zealand. No sequence sharing was observed between members of different species, and congeneric species showed from 2.3 to 19.5% divergence. Sequence divergence among members of a species was typically low (mean = 0.7%; range 0.0–8.5%), but two species showed intraspecific divergences in excess of 2%. Phylogenetic reconstructions based on COI were largely congruent with previous conclusions based on morphology, although the sequence data did not support placement of the purse-cased caddisflies (Hydroptilidae) within the uncased caddisflies, and, in particular, the Rhyacophiloidea. We conclude that sequence variation in the COI gene locus is an effective tool for the identification of New Zealand caddisfly species, and can provide preliminary phylogenetic inferences. Further research is needed to ascertain the significance of the few instances of high intra-specific divergence and to determine if any instances of sequence sharing will be detected with larger sample sizes

Robustness Evaluation for Phylogenetic Reconstruction Methods and Evolutionary Models Reconstruction of Tumor Progression

During evolutionary history, genomes evolve by DNA mutation, genome rearrangement, duplication and gene loss events. There has been endless effort to the phylogenetic and ancestral genome inference study. Due to the great development of various technology, the information about genomes is exponentially increasing, which make it possible figure the problem out. The problem has been shown so interesting that a great number of algorithms have been developed rigorously over the past decades in attempts to tackle these problems following different kind of principles. However, difficulties and limits in performance and capacity, and also low consistency largely prevent us from confidently statement that the problem is solved. To know the detailed evolutionary history, we need to infer the phylogeny of the evolutionary history (Big Phylogeny Problem) and also infer the internal nodes information (Small Phylogeny Problem). The work presented in this thesis focuses on assessing methods designed for attacking Small Phylogeny Problem and algorithms and models design for genome evolution history inference from FISH data for cancer data. During the recent decades, a number of evolutionary models and related algorithms have been designed to infer ancestral genome sequences or gene orders. Due to the difficulty of knowing the true scenario of the ancestral genomes, there must be some tools used to test the robustness of the adjacencies found by various methods. When it comes to methods for Big Phylogeny Problem, to test the confidence rate of the inferred branches, previous work has tested bootstrapping, jackknifing, and isolating and found them good resampling tools to corresponding phylogenetic inference methods. However, till now there is still no system work done to try and tackle this problem for small phylogeny. We tested the earlier resampling schemes and a new method inversion on different ancestral genome reconstruction methods and showed different resampling methods are appropriate for their corresponding methods. Cancer is famous for its heterogeneity, which is developed by an evolutionary process driven by mutations in tumor cells. Rapid, simultaneous linear and branching evolution has been observed and analyzed by earlier research. Such process can be modeled by a phylogenetic tree using different methods. Previous phylogenetic research used various kinds of dataset, such as FISH data, genome sequence, and gene order. FISH data is quite clean for the reason that it comes form single cells and shown to be enough to infer evolutionary process for cancer development. RSMT was shown to be a good model for phylogenetic analysis by using FISH cell count pattern data, but it need efficient heuristics because it is a NP-hard problem. To attack this problem, we proposed an iterative approach to approximate solutions to the steiner tree in the small phylogeny tree. It is shown to give better results comparing to earlier method on both real and simulation data. In this thesis, we continued the investigation on designing new method to better approximate evolutionary process of tumor and applying our method to other kinds of data such as information using high-throughput technology. Our thesis work can be divided into two parts. First, we designed new algorithms which can give the same parsimony tree as exact method in most situation and modified it to be a general phylogeny building tool. Second, we applied our methods to different kinds data such as copy number variation information inferred form next generation sequencing technology and predict key changes during evolution

Application of multiobjective genetic programming to the design of robot failure recognition systems

We present an evolutionary approach using multiobjective genetic programming (MOGP) to derive optimal feature extraction preprocessing stages for robot failure detection. This data-driven machine learning method is compared both with conventional (nonevolutionary) classifiers and a set of domain-dependent feature extraction methods. We conclude MOGP is an effective and practical design method for failure recognition systems with enhanced recognition accuracy over conventional classifiers, independent of domain knowledge