dorsal/arxiv
View SchemaSUMO Substrates and Sites Prediction Combining Pattern Recognition and Phylogenetic Conservation
| Authors | Yu Xue, Fengfeng Zhou, Hualei Lu, Guoliang Chen, Xuebiao Yao |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0409011 |
| URL | https://arxiv.org/abs/q-bio/0409011 |
Abstract
Small Ubiquitin-related modifier (SUMO) proteins are widely expressed in eukaryotic cells, which are reversibly coupled to their substrates by motif recognition, called sumoylation. Two interesting questions are 1) how many potential SUMO substrates may be included in mammalian proteomes, such as human and mouse, 2) and given a SUMO substrate, can we recognize its sumoylation sites? To answer these two questions, previous prediction systems of SUMO substrates mainly adopted the pattern recognition methods, which could get high sensitivity with relatively too many potential false positives. So we use phylogenetic conservation between mouse and human to reduce the number of potential false positives.
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"abstract": "Small Ubiquitin-related modifier (SUMO) proteins are widely expressed in\neukaryotic cells, which are reversibly coupled to their substrates by motif\nrecognition, called sumoylation. Two interesting questions are 1) how many\npotential SUMO substrates may be included in mammalian proteomes, such as human\nand mouse, 2) and given a SUMO substrate, can we recognize its sumoylation\nsites? To answer these two questions, previous prediction systems of SUMO\nsubstrates mainly adopted the pattern recognition methods, which could get high\nsensitivity with relatively too many potential false positives. So we use\nphylogenetic conservation between mouse and human to reduce the number of\npotential false positives.",
"arxiv_id": "q-bio/0409011",
"authors": [
"Yu Xue",
"Fengfeng Zhou",
"Hualei Lu",
"Guoliang Chen",
"Xuebiao Yao"
],
"categories": [
"q-bio.GN"
],
"title": "SUMO Substrates and Sites Prediction Combining Pattern Recognition and Phylogenetic Conservation",
"url": "https://arxiv.org/abs/q-bio/0409011"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "92676ba0-01f0-42ba-b3c1-43012c8bc446",
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"type": "Model",
"variant": "snapshot-2026-03-01",
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