Abstract:
OBJECTIVE:A major focus in computational system biology research is defining organizing principles that govern complex biological network formation and evolution. The task is considered a major challenge because network behavior and function prediction requires the identification of functionally and statistically important motifs. Here we propose an algorithm for performing two tasks simultaneously: (a) detecting global statistical features and local connection structures in biological networks, and (b) locating functionally and statistically significant network motifs. METHODS AND MATERIAL:Two gene regulation networks were tested: the bacteria Escherichia coli and the yeast eukaryote Saccharomyces cerevisiae. To understand their structural organizing principles and evolutionary mechanisms, we defined bridge motifs as composed of weak links only or of at least one weak link and multiple strong links, and defined brick motifs as composed of strong links only. RESULTS:After examining functional and topological differences between bridge and brick motifs for predicting biological network behaviors and functions, we found that most genetic network motifs belong to the bridge category. This strongly suggests that the weak-tie links that provide unique paths for signal control significantly impact the signal processing function of transcription networks. CONCLUSIONS:Bridge and brick motif content analysis can provide researchers with global and local views of individual real networks and help them locate functionally and topologically overlapping or isolated motifs for purposes of investigating biological system functions, behaviors, and similarities.
journal_name
Artif Intell Medjournal_title
Artificial intelligence in medicineauthors
Huang CY,Cheng CY,Sun CTdoi
10.1016/j.artmed.2007.07.006subject
Has Abstractpub_date
2007-10-01 00:00:00pages
117-27issue
2eissn
0933-3657issn
1873-2860pii
S0933-3657(07)00095-4journal_volume
41pub_type
杂志文章abstract:OBJECTIVE:Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2014.06.003
更新日期:2014-09-01 00:00:00
abstract::In this study different substitution methods for the replacement of missing data values were inspected for the use of these cases in a neural network based decision support system for acute appendicitis. The leucocyte count had the greatest number of missing values and was used in the analyses. Four different methods ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(98)00027-x
更新日期:1998-07-01 00:00:00
abstract:OBJECTIVE:This paper identifies and reviews ethical issues associated with artificial intelligent care providers (AICPs) in mental health care and other helping professions. Specific recommendations are made for the development of ethical codes, guidelines, and the design of AICPs. METHODS:Current developments in the ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2014.06.004
更新日期:2014-09-01 00:00:00
abstract:OBJECTIVE:New medical systems may be rejected by staff because they do not integrate with local practice. An expert system, FLORENCE, is being developed to help staff in a neonatal intensive care unit (NICU) make decisions about ventilator settings when treating babies with respiratory distress syndrome. For FLORENCE t...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2005.01.004
更新日期:2005-11-01 00:00:00
abstract::Traditional Chinese medicine has developed over more than 4000 years. A tremendous amount of medical knowledge has been accumulated, among which herbal drugs and formulae are an important portion. This paper presents an ontology for traditional Chinese drugs and formulae, and an ontology-based system for extracting kn...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.01.015
更新日期:2004-09-01 00:00:00
abstract::This paper describes a methodology for achieving an efficient implementation of clinical practice guidelines. Three main steps are illustrated: knowledge representation, model simulation and implementation within a health care organisation. The resulting system can be classified as a 'guideline-based careflow manageme...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(00)00050-6
更新日期:2000-08-01 00:00:00
abstract::An object-oriented approach has been applied to the different stages involved in developing a knowledge base about insulin metabolism. At an early stage the separation of terminological and assertional knowledge was made. The terminological component was developed by medical experts and represented in CORE. An object-...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/0933-3657(94)90025-6
更新日期:1994-12-01 00:00:00
abstract::Rough sets (Pawlak Z. Rough Sets: Theoretical Aspects of Reasoning about Data, Dordrecht: Kluwer Academic Publishers, 1991) is a relatively new approach to representing and reasoning with incomplete and uncertain knowledge. This article introduces the basic concepts of rough sets and Boolean reasoning (Brown FM. Boole...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(98)00051-7
更新日期:1999-02-01 00:00:00
abstract::Incorporating prior knowledge into black-box classifiers is still much of an open problem. We propose a hybrid Bayesian methodology that consists in encoding prior knowledge in the form of a (Bayesian) belief network and then using this knowledge to estimate an informative prior for a black-box model (e.g. a multilaye...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(03)00053-8
更新日期:2003-09-01 00:00:00
abstract:OBJECTIVE:Sketching is ubiquitous in medicine. Physicians commonly use sketches as part of their note taking in patient records and to help convey diagnoses and treatments to patients. Medical students frequently use sketches to help them think through clinical problems in individual and group problem solving. Applicat...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2006.07.010
更新日期:2007-02-01 00:00:00
abstract:OBJECTIVE:One of the major topics towards robot consciousness is to give a robot the capabilities of self-consciousness. We propose that robot self-consciousness is based on higher order perception of the robot, in the sense that first-order robot perception is the immediate perception of the outer world, while higher ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2008.07.003
更新日期:2008-10-01 00:00:00
abstract:OBJECTIVE:Protein homology prediction between protein sequences is one of critical problems in computational biology. Such a complex classification problem is common in medical or biological information processing applications. How to build a model with superior generalization capability from training samples is an ess...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2005.02.003
更新日期:2005-09-01 00:00:00
abstract:OBJECTIVE:The problem of designing and managing teams of workers that can collaborate working together towards common goals is a challenging one. Incomplete or ambiguous specification of responsibilities and accountabilities, lack of continuity in teams working in shifts, inefficient organization of teams due to lack o...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2011.08.005
更新日期:2011-11-01 00:00:00
abstract::In this paper, we describe a system for automating the diagnosis of myocardial perfusion from single-photon emission computerized tomography (SPECT) images of male and female hearts. Initially we had several thousand of SPECT images, other clinical data and physician-interpreter's descriptions of the images. The image...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(02)00055-6
更新日期:2002-09-01 00:00:00
abstract::Early recognition of heart disease plays a vital role in saving lives. Heart murmurs are one of the common heart problems. In this study, Artificial Neural Network (ANN) is trained with Modified Neighbor Annealing (MNA) to classify heart cycles into normal and murmur classes. Heart cycles are separated from heart soun...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2017.05.005
更新日期:2017-05-01 00:00:00
abstract::We describe an approach for developing knowledge-based medical decision support systems based on the new technology of case-based reasoning. This work is based on the results of the Inreca European project and preliminary results from the Inreca + project which mainly deals with medical applications. One goal was to s...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(97)00038-9
更新日期:1998-01-01 00:00:00
abstract:MOTIVATIONS:It has recently been argued [1] that the effectiveness of a cure depends on the doctor-patient shared understanding of an illness and its treatment. Although a better communication between doctor and patient can be pursued through dedicated training programs, or by collecting patients' experiences and sympt...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2019.101727
更新日期:2019-11-01 00:00:00
abstract:OBJECTIVE:The successful preparation of cells for therapy depends on the characterization of causal factors affecting cell quality. Ultra scale-down methods are used to characterize cells in terms of their response to process engineering causal factors of hydrodynamic shear stress and time. This response is in turn cha...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2014.07.003
更新日期:2014-10-01 00:00:00
abstract::The purpose of a clinical trial is to evaluate a new treatment procedure. When medical researchers conduct a trial, they recruit participants with appropriate health problems and medical histories. To select participants, they analyze medical records of the available patients, which has traditionally been a manual pro...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.01.017
更新日期:2004-07-01 00:00:00
abstract:OBJECTIVE:Arden Syntax is a standard for representing and sharing medical knowledge in form of independent modules and looks back on a history of 25 years. Its traditional field of application is the monitoring of clinical events such as generating an alert in case of occurrence of a critical laboratory result. Arden S...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2015.09.003
更新日期:2018-11-01 00:00:00
abstract::A capsule endoscopy examination of the human small bowel generates a large number of images that have high similarity. In order to reduce the time it takes to review the high similarity images, clinicians will increase the playback speed, typically to 15 frames per second [1]. Associated with this behaviour is an incr...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2018.12.008
更新日期:2019-03-01 00:00:00
abstract:OBJECTIVE:While EIRA has proved to be successful in the detection of anomalous patient responses to treatments in the Intensive Care Unit, it could not describe to clinicians the rationales behind the anomalous detections. The aim of this paper is to address this problem. METHODS:Few attempts have been made in the pas...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2013.02.003
更新日期:2013-05-01 00:00:00
abstract::This paper presents a computer-based model for differential diagnosis of specific language impairment (SLI), a language disorder that, in many cases, cannot be easily diagnosed. This difficulty necessitates the development of a methodology to assist the speech therapist in the diagnostic process. The methodology tool ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(02)00076-3
更新日期:2003-11-01 00:00:00
abstract:OBJECTIVE:Develop and evaluate a natural language processing application for classifying chief complaints into syndromic categories for syndromic surveillance. INTRODUCTION:Much of the input data for artificial intelligence applications in the medical field are free-text patient medical records, including dictated med...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.04.001
更新日期:2005-01-01 00:00:00
abstract:OBJECTIVES:We present in this article experiments on multi-language information extraction and access in the medical domain. For such applications, multilingual terminology plays a crucial role when working on specialized languages and specific domains. MATERIAL AND METHODS:We propose firstly a method for enriching mu...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2004.07.015
更新日期:2005-02-01 00:00:00
abstract::Automatic arrhythmia detection based on electrocardiogram (ECG) is of great significance for early prevention and diagnosis of cardiac diseases. Recently, deep learning methods have been applied to arrhythmia detection and obtained great success. Among them, convolutional neural network (CNN) is an effective method fo...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2020.101856
更新日期:2020-06-01 00:00:00
abstract:OBJECTIVE:Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2009.07.012
更新日期:2010-02-01 00:00:00
abstract:OBJECTIVE:The aim of this paper is to study the feasibility and the performance of some classifier systems belonging to family of instance-based (IB) learning as second-opinion diagnostic tools and as tools for the knowledge extraction phase in the process of knowledge discovery in clinical databases. MATERIALS AND ME...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2011.04.002
更新日期:2011-07-01 00:00:00
abstract:OBJECTIVE:We present a combined terminological resource for text mining over biomedical literature. The purpose of the resource is to allow the detection of mentions of specific biological entities in scientific publications, and their grounding to widely accepted identifiers. This is an essential process, useful in it...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/j.artmed.2011.04.011
更新日期:2011-06-01 00:00:00
abstract::Allowing exchange of information and cooperation among network-wide distributed and heterogeneous applications is a major need of current health-care information systems. The European project SynEx aims at developing an integration platform for both new and legacy applications on each partner's site. We developed, in ...
journal_title:Artificial intelligence in medicine
pub_type: 杂志文章
doi:10.1016/s0933-3657(03)00007-1
更新日期:2003-03-01 00:00:00