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Intuitive and machine understandable representation of the - - PowerPoint PPT Presentation

Nov 19, 2022 39 likes •682 views

Intuitive and machine understandable representation of the bioinformatics domain and of related resources with Resourceomes Nicola Cannata, Flavio Corradini, Sergio Gabrielli, Luana Leoni, Emanuela Merelli, Francesca Piersigilli, Leonardo Vito

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Intuitive and machine understandable representation of the bioinformatics domain and

  • f related resources with Resourceomes

Nicola Cannata, Flavio Corradini, Sergio Gabrielli, Luana Leoni, Emanuela Merelli, Francesca Piersigilli, Leonardo Vito

  • Mathematic and Computer Science Department,

University of Camerino, Italy

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How many minutes (hours) do we spend every day in Google and bibliographic searches?

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In life sciences and “-omics” disciplines we are becoming used to deluges and overflows…

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The data overflow…

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Besides data overflow we are experimenting also resources overflow. E.g. academic Articles,…

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Now science is becoming e-science…

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Will e-science become g-science…?

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Databases are essential resources for bioinformatics

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201 86 1999 226 95 2000 281 73 2001 335 94 2002 386 95 2003 548 142 2004 719 137 2005 858 164 2006 968 174 2007 DB listed Articles Year

Database special issue Nucleic Acids Research (NAR) - Oxford Journals

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Web Servers are common tools for bioinformaticians

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Articles published “ONLY” from main bioinformatics journals

BMC Journal of PLoS Computational Briefings IEEE Trans. Applied Int.J.of Bioinf. Computational Computational Biology in

  • Comp. Biol. And

Res.& Appl. Biology Biology and Chemistry Bioinformatics Bioinformatics (IJBRA) 2005 900 414 83 61 58 47 34 32 32 2004 627 209 69 53 40 22 24 2003 534 66 61 71 35 2002 365 40 52 77 41 2001 245 9 39 66 31 2000 178 1 52 72 33 Year Bioinformatics Bioinformatics Bioinformatics

100 200 300 400 500 600 700 800 900 2005 2004 2003 2002 2001 2000 Year Articles

Bioinformatics BMC Bioinformatics Journal of Computational Biology Computational Biology and Chemistry Briefings in Bioinformatics IEEE Trans. Comp. Biol. And Bioinformatics Applied Bioinformatics PLoS Computational Biology Int.J.of Bioinf. Res.& Appl. (IJBRA)

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Bioinformatics is evolving

“IN SILICO EXPERIMENTS” From command line… (till 90s) to web interfaces and (perl) scripts… (with the advent of the WWW) To Web Services and workflows (now)

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In this new bioinformatics Web Services play a key

  • role. Programs interact with programs on the web…
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Why to search for resources?

  • you have to develop a program, a database,

possibly avoiding to re-invent the wheel…

  • interdisciplinarity…

introduction to a new domain. Obtain a fast overview

  • f a (new, for you) scientific domain (preferably in a

visual fashion)

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So, where to search for (bioinformatics) resources

  • that of course you are not aware of - ?
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In search engines?… Good luck!

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In specialized web sites? … First, find them!

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In SIG web sites? … Are they updated?

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In the literature? … When do you need them?

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And also when articles are detected, maybe the presented resources are not there anymore!

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In the age of WWW resources appear… and disappear

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If you are lucky you can find some nice and intuitive reviews

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What’s with the “staying updated”?

  • TOC e-mail services
  • Subject alert services
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Resource directories are good place to start…

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But the amount of resources and their variety require that directories would be machine understandable

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Intelligent software agents will then be able to “reason”

  • n the resources and to easily find them for you
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Two “orthogonal” classifications

  • resources should be classified according their nature

(a program, a database, a paper, a person…) and according what they refer to, what they are for

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Computer science subjects can be classified…

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As well as Mathematics subjects

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But for Bioinformatics (and Life Sciences in general) is not existing any shared classification schema of the domain. And life scientists like taxonomies…

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BioInformatics SystemsBiology Structural Bioinformatics Genome Analysis Sequence Analysis Phylogenetics Genetics Population Analysis Databases And Ontologies Gene Expression Data And Text Mining IsA IsA IsA IsA IsA IsA IsA IsA IsA

The classification introduced for articles of “Oxford’s Bioinformatics” in 2005

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Resource Ontology

Concerns Concerns

C

  • n

c e r n s

Domain Ontology

Our proposal: Resourceomes

A Resourceomes permits to arrange in an intuitive (for humans) and machine-understandable (for SW) manner the perceived structure of a domain and to “stick” resources (with their semantic relationships) to concepts of the domain

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This is just our first prototype of resource ontology

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Actor Literature resource Artifact

Publishes Creates CollaboratesWith

Literature resource Resource

Describes Cites

Examples of semantic relationships between resources

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Better this representation…

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… or this one?

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A web-based semantic browser for Resourceomes

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The first prototype of our browser

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Passing with the mouse over the icons you can see a description and the URI of the resource

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Many open issues:

  • Annotation of resources (manual, semi-automatic,

automatic)

  • Representation of the domain (ontology, concept

maps, topic maps, SKOS?)

  • Ranking of resources (page rank, judgments )
  • Status of resources (agents checking them)
  • Graph visualization? (GRAPPA – Graphviz)
  • Not only browser but also visual editor (GrOWL?)
  • …
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Acknowledgment

www.litbio.org

This work is supported by the Italian Investment Funds for Basic Research (FIRB) project “Laboratory of Interdisciplinary Technologies in Bioinformatics” (LITBIO).

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Hoping that the bioinformatics community could soon say

Thank you for your attention!