Engineering agent-mediated integration of bioinformatics analysis tools

Koutkias, Vassilis; Malousi, Andigoni; Maglaveras, Nicos

doi:10.3233/mgs-2007-3207

Cited by 5 publications

(11 citation statements)

References 41 publications

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“…The agent paradigm has been successfully employed in healthcare in various cases [37], with applications spanning from decision support systems [69], disease monitoring [70], telehealth services [71], ambient intelligence and independent living [72], integration of heterogeneous biomedical systems [73], cross-organisational workflow management [74], planning and resource allocation [75], to evaluation of medical systems [76]. Via this work, we illustrate a new application domain of agent technologies in life sciences, i.e.…”

Section: Related Workmentioning

confidence: 99%

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Koutkias

Jaulent

2015

J Med Syst

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Pharmacovigilance is the scientific discipline that copes with the continuous assessment of the safety profile of marketed drugs. This assessment relies on diverse data sources, which are routinely analysed to identify the so-called "signals", i.e. potential associations between drugs and adverse effects, that are unknown or incompletely documented. Various computational methods have been proposed to support domain experts in signal detection. However, recent comparative studies illustrated that current methods exhibit high false-positive rates, significantly variable performance across different datasets used for analysis and events of interest, but also complementarity in their outcomes. In this regard, in order to reinforce accurate and timely signal detection, we elaborated through an agent-based approach towards systematic, joint exploitation of multiple heterogeneous signal detection methods, data sources and other drug-related resources under a common, integrated framework. The approach relies on a multiagent system operating based on a collaborative agent interaction protocol, aiming to implement a comprehensive workflow that comprises of method selection and execution, as well as outcomes' aggregation, filtering, ranking and annotation. This paper presents the design of the proposed multiagent system, discusses implementation issues and demonstrates the applicability of the proposed solution in an example signal detection scenario. This work constitutes a step towards large-scale, integrated and knowledge-intensive computational signal detection.

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Section: Related Workmentioning

confidence: 99%

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

Koutkias

Jaulent

2015

J Med Syst

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“…Decomposition of complex problems into autonomous agents is an effective way of partitioning a problem [11]. In the systems where using different data resources and need an ontology, multi-agent technology has been adopted in several research projects for integration of Bioinformatics resources [12].…”

Section: Agent Technologymentioning

confidence: 99%

A Decision Support System Based on Multi-Agent Technology for Gene Expression Analysis

Marquez¹,

Savage²,

Berúmen³

et al. 2015

IJIS

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The genetic microarrays give to researchers a huge amount of data of many diseases represented by intensities of gene expression. In genomic medicine gene expression analysis is guided to find strategies for prevention and treatment of diseases with high rate of mortality like the different cancers. So, genomic medicine requires the use of complex information technology. The purpose of our paper is to present a multi-agent system developed in order to improve gene expression analysis with the automation of tasks about identification of genes involved in a cancer, and classification of tumors according to molecular biology. Agents that integrate the system, carry out reading files of intensity data of genes from microarrays, pre-processing of this information, and with machine learning methods make groups of genes involved in the process of a disease as well as the classification of samples that could propose new subtypes of tumors difficult to identify based on their morphology. Our results we prove that the multi-agent system requires a minimal intervention of user, and the agents generate knowledge that reduce the time and complexity of the work of prevention and diagnosis, and thus allow a more effective treatment of tumors.

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“…Apì thn upologistik skopi, h anlush biologik¸n dedomènwn perilambnei thn ulopoÐhsh algorijmik¸n mejìdwn pou diaqeirÐzontai eterogen dedomèna, ta opoÐa eÐnai apojhkeumèna se katanemhmènec Bseic Dedomènwn. Teqnik, h apotelesmatikìthta aut¸n twn mejìdwn periorÐzetai apì èlleiyh protupopoihmènwn mhqanism¸n antallag c dedomènwn kai koin apodekt c orologÐac gia thn perigraf twn dom¸n kai thc shmasiologÐac twn dedomènwn [86], [96].…”

Section: Eisagwgunclassified

“…Gia to skopì autì, kai lambnontac upìyh thn plhj¸ra twn sqetik¸n pìrwn (Bseic Dedomènwn kai ergaleÐa anlushc), qarakthrizìmenwn apì eterogèneia se dom kai shmasiologÐa, h angkh gia automatopoihmènec ektelèseic diadoqik¸n analÔsewn mèsa apì èna diamorfwmèno plaÐsio enopoÐhshc krÐnetai epitaktik [35]. Ap¸teroc, loipìn, stìqoc twn teqnik¸n enopoÐhshc sto sugkekrimèno pedÐo eÐnai h diafan c prìsbash se dedomèna kai katllhla ergaleÐa anlushc, me skopì thn exagwg nèac gn¸shc pou ja epitrèyei th dunatìthta apokruptogrfhshc twn mhqani-sm¸n pou kajorÐzoun th gonidiak èkfrash kai th sÔndes thc me pargontec pajogèneshc [96].…”

Section: Eisagwgunclassified

“…'Etsi, to katllhlo ergaleÐo apì kje kathgorÐa ja prèpei na epilegeÐ, sÔmfwna me tic apait seic anlushc pou jètei o qr sthc. Gia thn upost rixh autoÔ tou senarÐou enopoÐhshc kai thn ulopoÐhs tou me automatopoihmèno trìpo, proteÐnetai h endimesh arqitektonik praktìrwn dÔo epipèdwn tou Sqmatoc 5.4 [96]. Jewr¸ntac to sÔsthma pou parousisthke sthn pargrafo 5.3.1 wc epektsimh monda kai to sÔsthma thc paragrfou 5.3.2 wc epanaqrhsimopoi simh monda, h trèqousa arqitektonik epitrèpei (1) thn epilog tou katllhlou ergaleÐou apì kje klsh kai (2) to dunamikì orismì kai ektèlesh thc sqetik c ro c ergasi¸n, me ta ergaleÐa pou epilèqjhkan.…”

Section: Sôsthma Orizìntiac Kai Katakìrufhc Enopoðhshc Ergaleðwnunclassified

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Διαχείριση Και Επεξεργασία Πληροφορίας Σε Κατανεμημένα Ιατρικά Πληροφοριακά Συστήματα Με Αυτόνομους Πράκτορες Λογισμικού

Κουτκιάς¹

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ΜΙΧΑΗΛ-ΓΕΡΑΣΙΜΟΣ ΣΤΡΙΝΤΖΗΣ, ΚΑΘΗΓΗΤΗΣ ΚΩΝΣΤΑΝΤΙΝΟΣ ΠΑΠΠΑΣ, ΚΑΘΗΓΗΤΗΣ ΓΕΩΡΓΙΟΣ ΓΙΑΝΝΟΓΛΟΥ, ΑΝ. ΚΑΘΗΓΗΤΗΣ ∆ΗΜΗΤΡΙΟΣ ΚΟΥΦΟΓΙΑΝΝΗΣ, ΑΝ. ΚΑΘΗΓΗΤΗΣ ΑΝΑΣΤΑΣΙΟΣ ΝΤΕΛΟΠΟΥΛΟΣ, ΕΠ. ΚΑΘΗΓΗΤΗΣ «Η έγκριση της ∆ιδακτορικής ∆ιατριβής από τα προαναφερόµενα Τµήµατα του Αριστοτελείου Πανεπιστηµίου Θεσσαλονίκης, δεν υποδηλώνει αποδοχή των γνωµών του συγγραφέα».

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Engineering agent-mediated integration of bioinformatics analysis tools

Cited by 5 publications

References 41 publications

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

A Multiagent System for Integrated Detection of Pharmacovigilance Signals

A Decision Support System Based on Multi-Agent Technology for Gene Expression Analysis

Διαχείριση Και Επεξεργασία Πληροφορίας Σε Κατανεμημένα Ιατρικά Πληροφοριακά Συστήματα Με Αυτόνομους Πράκτορες Λογισμικού

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