oalib
Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
Integration of curated databases to identify genotype-phenotype associations
Chern-Sing Goh, Tara A Gianoulis, Yang Liu, Jianrong Li, Alberto Paccanaro, Yves A Lussier, Mark Gerstein
BMC Genomics , 2006, DOI: 10.1186/1471-2164-7-257
Abstract: Integrating the information in the two databases, we are able to correlate the presence or absence of a given protein in a microbe with its phenotype as measured by certain morphological characteristics or survival in a particular growth media. With a 0.8 correlation score threshold, 66% of the associations found were confirmed by the literature and at a 0.9 correlation threshold, 86% were positively verified.Our results suggest possible phenotypic manifestations for proteins biochemically associated with sugar metabolism and electron transport. Moreover, we believe our approach can be extended to linking pathogenic phenotypes with functionally related proteins.Traditionally, microbes have been identified on the basis of their response to a battery of phenotypic assays, for example, survival on a particular type of growth media or morphological characteristics. With the advent of high throughput sequencing efforts, over 300 microbes have been completely sequenced [1]. By integrating complex phenotypic data with sequence information, new phenotype-genotype relationships can be unveiled.The underpinnings for this work can be found in Marcotte et al. where phenotype was defined in terms of pathway membership which was used to predict protein function [2]. In addition, previous studies have proposed comparative genomic methods to predict characteristics such as hyperthermophily [3,4], flagellar motility [4-6], plant degradation [6], and pili assembly [4]. However, most of these studies focus on a few specific phenotypes within certain organisms [3-5]. Korbel et al. proposed an automated method to make word-species associations retrieved from Medline abstracts [6]. Here we introduce a new approach for discovering phenotype-genotype relationships using a clinical information database consisting of manually curated results from 93 phenotypic assays allowing for a large-scale analysis of phenotype-genotype relationships.The Global Infectious Diseases & Epidemiology Network
The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain
Tudor Groza, Jane Hunter, Andreas Zankl
BMC Bioinformatics , 2012, DOI: 10.1186/1471-2105-13-50
Abstract: We introduce the design considerations and implementation details of the Bone Dysplasia Ontology. We also describe the different components of the ontology, including a comprehensive and formal representation of the skeletal dysplasia domain as well as the related genotypes and phenotypes. We then briefly describe SKELETOME, a community-driven knowledge curation platform that is underpinned by the Bone Dysplasia Ontology. SKELETOME enables domain experts to use, refine and extend and apply the ontology without any prior ontology engineering experience--to advance the body of knowledge in the skeletal dysplasia field.The Bone Dysplasia Ontology represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.Skeletal dysplasias are a heterogeneous group of genetic disorders affecting skeletal development. There are currently over 450 recognised types, clustered in 40 groups. Patients with skeletal dysplasias have complex medical issues including short stature, degenerative joint disease, scoliosis and neurological complications. These patients are also a precious resource for biomedical research as they enable scientists to study the effects of single genes on human bone and cartilage development and function. The resulting insights lead to a better understanding of the pathogenesis of more common connective tissue disorders such as arthritis or osteoporosis.Despite their importance, bone dysplasias are not exploited to their full potential in biomedical research. Since most conditions are rare (< 1:10'000 b
Bridging the Gap between Genotype and Phenotype via Network Approaches  [PDF]
Yoo-Ah Kim,Teresa M. Przytycka
Frontiers in Genetics , 2013, DOI: 10.3389/fgene.2012.00227
Abstract: In the last few years we have witnessed tremendous progress in detecting associations between genetic variations and complex traits. While genome-wide association studies have been able to discover genomic regions that may influence many common human diseases, these discoveries created an urgent need for methods that extend the knowledge of genotype-phenotype relationships to the level of the molecular mechanisms behind them. To address this emerging need, computational approaches increasingly utilize a pathway-centric perspective. These new methods often utilize known or predicted interactions between genes and/or gene products. In this review, we survey recently developed network based methods that attempt to bridge the genotype-phenotype gap. We note that although these methods help narrow the gap between genotype and phenotype relationships, these approaches alone cannot provide the precise details of underlying mechanisms and current research is still far from closing the gap.
Bridging scales in cancer progression: Mapping genotype to phenotype using neural networks  [PDF]
Philip Gerlee,Eunjung Kim,Alexander R. A. Anderson
Quantitative Biology , 2014,
Abstract: In this review we summarize our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to characterise different aspects of the mapping from a cancer cells genotype and environment to its phenotype. Our central premise is that cancer is an evolving system subject to mutation and selection, and the primary conduit for these processes to occur is the cancer cell whose behaviour is regulated on multiple biological scales. The selection pressure is mainly driven by the microenvironment that the tumour is growing in and this acts directly upon the cell phenotype. In turn, the phenotype is driven by the intracellular pathways that are regulated by the genotype. Integrating all of these processes is a massive undertaking and requires bridging many biological scales (i.e. genotype, pathway, phenotype and environment) that we will only scratch the surface of in this review. We will focus on models that use neural networks as a means of connecting these different biological scales, since they allow us to easily create heterogeneity for selection to act upon and importantly this heterogeneity can be implemented at different biological scales. More specifically, we consider three different neural networks that bridge different aspects of these scales and the dialogue with the micro-environment, (i) the impact of the micro-environment on evolutionary dynamics, (ii) the mapping from genotype to phenotype under drug-induced perturbations and (iii) pathway activity in both normal and cancer cells under different micro-environmental conditions.
Estimation of Genetic Effects and Genotype-Phenotype Maps
Arnaud Le Rouzic,José M. álvarez-Castro
Evolutionary Bioinformatics , 2008,
Abstract: Determining the genetic architecture of complex traits is a necessary step to understand phenotypic changes in natural, experimental and domestic populations. However, this is still a major challenge for modern genetics, since the estimation of genetic effects tends to be complicated by genetic interactions, which lead to changes in the effect of allelic substitutions depending on the genetic background. Recent progress in statistical tools aiming to describe and quantify genetic effects meaningfully improves the efficiency and the availability of genotype-to-phenotype mapping methods. In this contribution, we facilitate the practical use of the recently published ‘NOIA’ quantitative framework by providing an implementation of linear and multilinear regressions, change of reference operation and genotype-to-phenotype mapping in a package (‘noia’) for the software R, and we discuss theoretical and practical benefits evolutionary and quantitative geneticists may find in using proper modeling strategies to quantify the effects of genes
A condition for the genotype-phenotype mapping: Causality  [PDF]
Bernhard Sendhoff,Martin Kreutz,Werner von Seelen
Physics , 1997,
Abstract: The appropriate choice of the genotype-phenotype mapping in combination with the mutation operator is important for a successful evolutionary search process. We suggest a measure to quantify the quality of this combination by addressing the question whether the relation among distances is carried over from one space to the other. Search processes which do not destroy the neighbourhood structure are termed strongly causal. We apply the proposed measure to parameter and structure optimisation problems in order to assess the combination (mapping, mutation operator) and at the same time to be able to propose improved settings.
Effect of Mutation and Recombination on the Genotype-Phenotype Map  [PDF]
C. R. Stephens
Physics , 2000,
Abstract: The effect of genetic operators other than selection, such as mutation and recombination, on the genotype-phenotype map is considered. In particular, when the genotypic fitness landscape exhibits a ``symmetry'', i.e. many genotypes corresponding to the same phenotype have equal fitness values, it is shown that such operators can break this symmetry. The consequences of this ``induced symmetry breaking'' are investigated. Specifically, it is shown that it generically leads to an increase in order or self-organization in the system and to the phenomenon of orthogenesis. Additionally, it is shown that it potentially leads to a more robust evolution circumventing some of the problems of brittleness. The above points are supported by explicit, analytic results associated with some simple one and two-locus models and also by some much more complicated numerical simulations.
Orodental phenotype and genotype findings in all subtypes of hypophosphatasia
Amélie Reibel, Marie-Cécile Manière, Fran?ois Clauss, Dominique Droz, Yves Alembik, Etienne Mornet, Agnès Bloch-Zupan
Orphanet Journal of Rare Diseases , 2009, DOI: 10.1186/1750-1172-4-6
Abstract: The purpose of this study was to document the oral features of HP patients and to relate theses features to the six recognized forms of HP in 5 patients with known genotype and to investigate the genotype-phenotype correlations.Clinical and radiographic examinations were carried out. We collected medical and dental history in the kindred and biochemical data. Finally, mutations in the ALPL gene were tested by DNA sequencing in SESEP laboratory.We have for the first time related the known dental anomalies which occur as integral features of HP to the recognized clinical forms of HP. We also pointed out striking dental abnormalities which were never described in association with this rare disease. Accurate genotype-phenotype severity correlations were observed.This work allowed us to compare orodental manifestations in all the clinical forms of HP within the patient's sample. According to the severity of the disorder, some dental defects were infrequent, while other were always present. The long term prognosis of the permanent teeth varies from a patient to another. As premature loss of primary teeth is often the first, and sometimes the only visible symptom of the milder forms, the paediatric dentist plays a critical role in the detection and diagnosis of the disease.Hypophosphatasia (HP) is an inherited disorder characterized by defective bone and tooth mineralization. HP is due to mutations in the liver/bone/kidney alkaline phosphatase gene (ALPL, MIM 171760) encoding the tissue-nonspecific alkaline phosphatase (TNAP) [1,2].The disease is highly variable in its clinical expression, due to strong allelic heterogeneity in the ALPL gene. More than 190 mutations have been described and most of them (79%) are missense mutations. This diversity results in highly variable clinical expressivity and in a great number of compound heterozygous genotypes [3].Clinical expression ranges from the extremes of stillbirth without mineralized bone to the isolated premature loss of pr
Integrating phenotype ontologies across multiple species
Christopher J Mungall, Georgios V Gkoutos, Cynthia L Smith, Melissa A Haendel, Suzanna E Lewis, Michael Ashburner
Genome Biology , 2010, DOI: 10.1186/gb-2010-11-1-r2
Abstract: The completion of the Human Genome Project [1,2] has resulted in an increase in high-throughput systematic projects aimed at elucidating the molecular basis of human disease. Accurate, precise, and comparable phenotypic information is critical for gaining an in-depth understanding of the relationship between diseases and genes, as well as shedding light upon the influence of different environments on individual genotypes. Natural language free-text descriptions allow for maximum expressivity, but the results are difficult to compute over. Structured controlled vocabularies and ontologies provide an alternative means of recording phenotypes in a way that combines a large degree of expressivity with the benefits of computability. A number of different ontologies have been developed for describing phenotypes, and whilst this is a welcome improvement over free-text descriptions, one problem is that these ontologies are developed for use within a particular project or species, and are not mutually interoperable. This means that it is difficult or extremely difficult to combine genotype-phenotype data from multiple databases - for example, if we wanted to search a mouse or zebrafish database for genes associated with a particular set of phenotypes associated with a human disease, this would require mapping between the individual phenotype ontologies.If we are to combine the results of a variety of phenotypic studies, then phenotypes need to be recorded in a structured systematic fashion. At the same time, the system must allow for a high degree of expressivity to capture the wide range of phenotypes observed across a variety of organisms and types of investigation. Here we propose a methodology that can be used to add value to existing phenotype ontologies by mapping them to a common reference framework based on existing standard ontologies. We implement this methodology for four active phenotype ontologies, focusing primarily on a phenotype ontology used for the mouse. O
The Electronic Medical Record (EMR)  [PDF]
PeterChris Okpala
Journal of Applied Medical Sciences , 2013,
Abstract: The electronic medical record (EMR) comprises a system of recording, processing, storing, recording and transferring health information electronically. Through the use of the EMR, several limitations that are associated with the paper-based medical record system are clearly overcome. For example, in contrast to the paper record, the EMR can play a larger role in medical decision-making, integrating the services of various departments, customizing care to the patients, reducing medical errors, improving quality, reducing costs, etc. In addition, the EMR can effectively help to transfer patient information from one organization to another and in this way help in referrals and improving the access to healthcare. This article examines the problems associated with the implementation of EMR systems, and later discusses the uses of EMRs and its benefits. If EMR system is implemented and used properly, it will help in the improvement of community health.
Page 1 /100
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.