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OMAMO: orthology-based model organism selection

Nicheperovich, A.; Altenhoff, A. M.; Dessimoz, C.; Majidian, S.

2021-11-05 bioinformatics
10.1101/2021.11.04.467067 bioRxiv
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SummaryThe conservation of pathways and genes across species has allowed scientists to use non-human model organisms to gain a deeper understanding of human biology. However, the use of traditional model systems such as mice, rats, and zebrafish is costly, time-consuming and increasingly raises ethical concerns, which highlights the need to search for less complex model organisms. Existing tools only focus on the few well-studied model systems, most of which are complex animals. To address these issues, we have developed Orthologous Matrix and Model Organisms, a software and a website that provide the user with the best simple organism for research into a biological process of interest based on orthologous relationships between the human and the species. The outputs provided by the database were supported by a systematic literature review. Availability and implementationhttps://omabrowser.org/omamo/, https://github.com/DessimozLab/omamo Contactchristophe.dessimoz@unil.ch and sina.majidian@unil.ch

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
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Top 0.7%
26.6%
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2
BMC Bioinformatics
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11.9%
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3
Nucleic Acids Research
◐ 1281 papers in training set
Top 3%
6.7%
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4
Bioinformatics Advances
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Top 1%
4.5%
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5
NAR Genomics and Bioinformatics
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Top 1%
4.0%
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50% of probability mass above
6
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◐ 61 papers in training set
Top 0.2%
3.2%
7
PeerJ
◐ 308 papers in training set
Top 2%
3.2%
8
GENETICS
◐ 483 papers in training set
Top 2%
2.4%
9
Scientific Reports
○ 3612 papers in training set
Top 49%
1.9%
10
Journal of Molecular Evolution
○ 22 papers in training set
Top 0.2%
1.7%
11
GigaScience
◐ 212 papers in training set
Top 3%
1.5%
12
Genome Biology and Evolution
◐ 338 papers in training set
Top 2%
1.5%
13
Microorganisms
○ 106 papers in training set
Top 2%
1.5%
14
BMC Biology
○ 265 papers in training set
Top 3%
1.1%
15
BMC Genomics
○ 406 papers in training set
Top 6%
1.1%
16
Frontiers in Bioinformatics
○ 49 papers in training set
Top 0.9%
1.1%
17
PLOS ONE
● 5266 papers in training set
Top 52%
1.1%
18
Biosystems
○ 31 papers in training set
Top 0.4%
1.1%
19
Genes
○ 144 papers in training set
Top 3%
1.1%
20
Journal of Computational Biology
○ 48 papers in training set
Top 0.8%
1.1%
21
Frontiers in Bioengineering and Biotechnology
○ 98 papers in training set
Top 2%
1.1%
22
Computational and Structural Biotechnology Journal
● 242 papers in training set
Top 5%
1.1%
23
Frontiers in Genetics
○ 230 papers in training set
Top 4%
1.0%
24
G3: Genes, Genomes, Genetics
◐ 252 papers in training set
Top 4%
0.9%
25
Computational Biology and Chemistry
○ 28 papers in training set
Top 1%
0.8%
26
eLife
● 5828 papers in training set
Top 66%
0.8%
27
Open Biology
● 106 papers in training set
Top 2%
0.8%
28
G3 Genes|Genomes|Genetics
◐ 351 papers in training set
Top 4%
0.8%
29
International Journal of Molecular Sciences
○ 494 papers in training set
Top 15%
0.8%
30
iScience
○ 1154 papers in training set
Top 41%
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.