36 lines
No EOL
1.6 KiB
TeX
36 lines
No EOL
1.6 KiB
TeX
\addtocounter{customchapter}{1}
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\chapter{Introduction}
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\input{abstract}
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A common usage of bipartite graphs in ecology is the representation of ecological
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interactions like
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plant-pollinator \parencite{ramos-jilibertoTopologicalChangeAndean2010},
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birds-seed dispersion, prey-predator or host-parasite
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\parencite{kaszewska-gilasGlobalStudiesHostParasite2021}. For plant-pollinator
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interactions, the rows are pollinator species and the columns are plant
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species,
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and the intersection is a value, binary if it is a presence/absence or a value
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if it is an abundance count.
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Some interesting results can arise when applying a tool widely used on a
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particular kind of interactions is used on another kind of interactions. In
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~\cite{desjardins-proulxEcologicalInteractionsNetflix2017} the authors use the
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\emph{K-nearest neighbour} (KNN) algorithm as a Recommender to predict missing
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preys for predators in a predator-prey network.\\
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Bipartite graphs are widely used in biology in general, in various fields, among
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which the previously cited ecological networks, but also in medicine with
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biomedical networks, biomolecular networks or epidemiological networks.
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\parencite{pavlopoulosBipartiteGraphsSystems2018}
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There is a need for comparison methods of bipartite networks in literature, and
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it is being actively developed,
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e.g.~\cite{pichonTellingMutualisticAntagonistic2024} use structures at multiple
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scales (species degree, motif frequency, nestedness \dots) to tell apart
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mutualistic and antagonistic networks.
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This motivates us to propose a model for structure detection in bipartite
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collections.
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% DONE Relu |