File size: 2,260 Bytes
b83473a
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
<!DOCTYPE html>
<html lang="en">
	<head>
		<meta charset="UTF-8" />
		<meta name="viewport" content="width=device-width, initial-scale=1.0" />
		<title>UniKP Kinetic Values Prediction</title>
		<script src="/static/index.js" defer></script>
		<link rel="stylesheet" type="text/css" href="/static/styles.css" />
	</head>
	<body>
		<h1>UniKP Kinetic Values Prediction</h1>
		<p> <a href="/docs" target="_blank">API Usage</a></p>
		<div class="box">
			<form id="predictionForm">
				<label for="sequence">Sequence:</label>
				<textarea id="sequence" name="sequence"></textarea>
				<label for="smiles">SMILES:</label><br />
				<textarea id="smiles" name="smiles"></textarea>
				<input type="submit" value="Submit" />
			</form>
		</div>
		<div id="predictionResults" class="box"></div>

		<div class="box">
			<h2>UniKP</h2>
			<h3>What is UniKP?</h3>
			<p>
				UniKP is a unified framework for the prediction of enzyme
				kinetic parameters. It is a machine learning model that predicts
				the kinetic parameters of enzymes based on their amino acid
				sequences and SMILES representations of a substrate.
			</p>
			<h3>Why is this interesting?</h3>
			<p>
				UniKP can be used to predict the kinetic parameters of enzymes,
				which can be used for feature extraction in enzyme engineering.
				Knowing the kinetic parameters of an enzyme can help to
				understand its function and can be used to optimize its
				performance.
			</p>
		</div>
		<div class="box">
			<h2>References</h2>
			<ul>
				<li>
					<a
						href="https://github.com/Luo-SynBioLab/UniKP"
						target="_blank"
						><img
							class="devicon"
							src="https://cdn.jsdelivr.net/gh/devicons/devicon@latest/icons/github/github-original-wordmark.svg"
							alt="UniKP"
					/></a>
				</li>
				<li>
					<a
						href="https://www.nature.com/articles/s41467-023-44113-1"
						target="_blank"
						>Yu, H., Deng, H., He, J. et al. UniKP: a unified
						framework for the prediction of enzyme kinetic
						parameters. Nat Commun 14, 8211 (2023)</a
					>
				</li>
				<li><a href="https://www.ml6.eu/" target="_blank">ML6</a></li>
				<li>
					<a href="https://www.decypher.bio/" target="_blank"
						>deCYPher</a
					>
				</li>
			</ul>
		</div>
	</body>
</html>