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5- < title > Machine Learning for Protein Design, AAAI 2025 Tutorial</ title >
5+ < title > Artificial Intelligence for Protein Design, AAAI 2025 Tutorial</ title >
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29- < h1 class ="title "> AAAI 2025 Tutorial< br > Machine Learning for Protein Design</ h1 >
29+ < h1 class ="title "> AAAI 2025 Tutorial< br > Artificial Intelligence for Protein Design</ h1 >
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@@ -156,16 +156,16 @@ <h2 id="outline">Outline</h2>
156156 </ li >
157157 < li > Structure Representation Learning
158158 < ul >
159- < li > Geometric Deep Learning</ li >
160- < li > Protein Structure Encoder [EGNN ( < a class =" citation " href =" #satorras2021egnn " > (Satorras et al., 2021) </ a > ), GVP ( < a class ="citation " href ="#jing2021gvp "> (Jing et al., 2021)</ a > ) , GearNet ( < a class ="citation " href ="#zhang2023gearnet "> (Zhang et al., 2023)</ a > ) , CDConv ( < a class ="citation " href ="#fan2023cdconv "> (Fan et al., 2023)</ a > ) ]
159+ < li > Geometric Deep Learning [EGNN < a class =" citation " href =" #satorras2021egnn " > (Satorras et al., 2021) </ a > ] </ li >
160+ < li > Protein Structure Encoder [GVP < a class ="citation " href ="#jing2021gvp "> (Jing et al., 2021)</ a > , GearNet < a class ="citation " href ="#zhang2023gearnet "> (Zhang et al., 2023)</ a > , CDConv < a class ="citation " href ="#fan2023cdconv "> (Fan et al., 2023)</ a > ]
161161 <!-- <ul>
162162 <li>EGNN [<a class="citation" href="#satorras2021egnn">(Satorras et al., 2021)</a>]</li>
163163 <li>GVP [<a class="citation" href="#jing2021gvp">(Jing et al., 2021)</a>]</li>
164164 <li>GearNet [<a class="citation" href="#zhang2023gearnet">(Zhang et al., 2023)</a>]</li>
165165 <li>CDConv [<a class="citation" href="#fan2023cdconv">(Fan et al., 2023)</a>]</li>
166166 </ul> -->
167167 </ li >
168- < li > Structure Pre-training Algorithm [GearNet ( < a class ="citation " href ="#zhang2023gearnet "> (Zhang et al., 2023)</ a > ) , SiamDiff ( < a class ="citation " href ="#zhang2023siamdiff "> (Zhang et al., 2023)</ a > ) ]
168+ < li > Structure Pre-training Algorithm [GearNet < a class ="citation " href ="#zhang2023gearnet "> (Zhang et al., 2023)</ a > , SiamDiff < a class ="citation " href ="#zhang2023siamdiff "> (Zhang et al., 2023)</ a > ]
169169 <!-- <ul>
170170 <li>GearNet [<a class="citation" href="#zhang2023gearnet">(Zhang et al., 2023)</a>]</li>
171171 <li>SiamDiff [<a class="citation" href="#zhang2023siamdiff">(Zhang et al., 2023)</a>]</li>
@@ -175,9 +175,9 @@ <h2 id="outline">Outline</h2>
175175 </ li >
176176 < li > Multi-Modality Representation Learning
177177 < ul >
178- < li > Sequence + Structure [ESM-GearNet ( < a class ="citation " href ="#zhang2023esmgearnet "> (Zhang et al., 2023)</ a > ) , SaProt ( < a class ="citation " href ="#su2023saprot "> (Su et al., 2023)</ a > ) , DPLM-2 ( < a class ="citation " href ="#wang2024dplm2 "> (Wang et al., 2024)</ a > ) ]</ li >
179- < li > Sequence + Text [ProtST ( < a class ="citation " href ="#xu2023protst "> (Xu et al., 2023)</ a > ) ]</ li >
180- < li > Sequence + Structure + Function [ESM3 ( < a class ="citation " href ="#hayes2024esm3 "> (Hayes et al., 2024)</ a > ) ]</ li >
178+ < li > Sequence + Structure [ESM-GearNet < a class ="citation " href ="#zhang2023esmgearnet "> (Zhang et al., 2023)</ a > , SaProt < a class ="citation " href ="#su2023saprot "> (Su et al., 2023)</ a > , DPLM-2 < a class ="citation " href ="#wang2024dplm2 "> (Wang et al., 2024)</ a > ]</ li >
179+ < li > Sequence + Text [ProtST < a class ="citation " href ="#xu2023protst "> (Xu et al., 2023)</ a > ]</ li >
180+ < li > Sequence + Structure + Function [ESM3 < a class ="citation " href ="#hayes2024esm3 "> (Hayes et al., 2024)</ a > ]</ li >
181181 </ ul >
182182 </ li >
183183 < li > Open Source Platform TorchProtein</ li >
@@ -349,7 +349,7 @@ <h2 id="references">References</h2>
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352- < h3 class ="footer-title "> Machine Learning for Protein Design, AAAI 2025 Tutorial</ h3 >
352+ < h3 class ="footer-title "> Artificial Intelligence for Protein Design, AAAI 2025 Tutorial</ h3 >
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