{"id":3386,"date":"2026-01-14T07:16:00","date_gmt":"2026-01-13T23:16:00","guid":{"rendered":"https:\/\/www.laoyulaoyu.com\/?p=3386"},"modified":"2026-01-05T23:18:47","modified_gmt":"2026-01-05T15:18:47","slug":"%e6%96%b0%e8%a7%86%e8%a7%92%e5%88%86%e4%ba%ab%ef%bc%9a%e7%94%a8%e5%87%a0%e4%bd%95%e6%8a%98%e5%8f%a0%e7%9c%8b%e6%87%82%e5%b8%82%e5%9c%ba%e5%99%aa%e9%9f%b3%e4%b8%8e%e4%bf%a1%e5%8f%b7","status":"publish","type":"post","link":"https:\/\/laoyulaoyu.com\/index.php\/2026\/01\/14\/%e6%96%b0%e8%a7%86%e8%a7%92%e5%88%86%e4%ba%ab%ef%bc%9a%e7%94%a8%e5%87%a0%e4%bd%95%e6%8a%98%e5%8f%a0%e7%9c%8b%e6%87%82%e5%b8%82%e5%9c%ba%e5%99%aa%e9%9f%b3%e4%b8%8e%e4%bf%a1%e5%8f%b7\/","title":{"rendered":"\u65b0\u89c6\u89d2\u5206\u4eab\uff1a\u7528\u201c\u51e0\u4f55\u6298\u53e0\u201d\u770b\u61c2\u5e02\u573a\u566a\u97f3\u4e0e\u4fe1\u53f7\uff08\u9644\u6e90\u7801\uff09"},"content":{"rendered":"\n

\u4f5c\u8005\uff1a\u8001\u4f59\u635e\u9c7c<\/a><\/p>\n\n\n\n

\u539f\u521b\u4e0d\u6613\uff0c\u8f6c\u8f7d\u8bf7\u6807\u660e\u51fa\u5904\u53ca\u539f\u4f5c\u8005\u3002<\/mark><\/strong><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n
\n
\u5199\u5728\u524d\u9762\u7684\u8bdd\uff1a<\/strong>\u4f5c\u4e3a\u4e00\u4e2a\u6570\u5b57\u91d1\u878d\u535a\u4e3b\u548c\u91cf\u5316\u56e2\u961f\u8d1f\u8d23\u4eba\uff0c\u6211\u603b\u7231\u627e\u65b0\u89d2\u5ea6\u770b\u5e02\u573a\u3002\u4eca\u5929\u5206\u4eab\u4e00\u4e2a\u6709\u8da3\u7684\u5185\u5bb9\uff1a\u5e02\u573a\u6298\u53e0<\/strong>\u3002\u5b83\u6765\u81ea\u8c37\u6b4cDeepMind\u7684\u86cb\u767d\u8d28\u6298\u53e0\u6a21\u578bAlphaFold\u7684\u542f\u53d1\u3002\u6211\u628a\u8fd9\u4e2a\u6982\u5ff5\u7528\u5728\u91d1\u878d\u4e0a\uff0c\u5e2e\u52a9\u5927\u5bb6\u4ece\u51e0\u4f55\u89d2\u5ea6\u7406\u89e3\u5e02\u573a\u53d8\u5316\u3002\u4e0d\u662f\u9884\u6d4b\u4ef7\u683c\uff0c\u800c\u662f\u770b\u6e05\u5e02\u573a\u7684\u6574\u4f53\u5f62\u72b6\u548c\u72b6\u6001\u3002<\/pre>\n<\/blockquote>\n\n\n\n
\u4e00\u3001<\/strong>\u4e3a\u4ec0\u4e48\u8981\u8bc6\u522b\u5e02\u573a\u72b6\u6001\uff1f<\/strong><\/h2>\n\n\n\n
\u5e02\u573a\u72b6\u6001\u8fd9\u4e1c\u897f\uff0c\u8bf4\u767d\u4e86\u5c31\u662f\u5224\u65ad\u73b0\u5728\u5e02\u573a\u5904\u4e8e\u5565”\u60c5\u7eea”\u4e2d\u3002\u60c5\u7eea\u7a33\u5b9a\u7684\u65f6\u5019\uff0c\u4ef7\u683c\u8df3\u52a8\u76f8\u5bf9\u6e29\u548c\uff1b\u60c5\u7eea\u4e0a\u5934\u7684\u65f6\u5019\uff0c\u4e0a\u8e7f\u4e0b\u8df3\u6ca1\u4e2a\u51c6\u3002<\/p>\n\n\n\n
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\u4ee5\u524d\u54b1\u4eec\u4e3b\u8981\u9760\u89c2\u5bdf\u6ce2\u52a8\u7387\u3001\u5747\u7ebf\u8fd9\u4e9b\u6307\u6807\u6765\u5224\u65ad\u3002\u4f46\u95ee\u9898\u662f\uff0c\u8fd9\u4e9b\u6307\u6807\u90fd\u662f\u4e00\u7ef4\u7684\uff0c\u800c\u4e14\u628a\u4ef7\u683c\u5e8f\u5217\u5f53\u6210\u72ec\u7acb\u70b9\u6765\u5904\u7406\uff0c\u5ffd\u7565\u4e86\u4ef7\u683c\u53d8\u5316\u7684\u5148\u540e\u987a\u5e8f\u3002<\/p>\n\n\n\n
\u800c\u201c<\/strong>\u5e02\u573a\u6298\u53e0\u201d<\/strong>\u8fd9\u4e2a\u60f3\u6cd5\u662f\u4ece\u751f\u7269\u5b66\u501f\u6765\u3002\u86cb\u767d\u8d28\u662f\u6c28\u57fa\u9178\u94fe\uff0c\u6298\u53e0\u6210\u4e09\u7ef4\u5f62\u72b6\u624d\u5de5\u4f5c\u3002AlphaFold\u7528AI\u9884\u6d4b\u8fd9\u4e2a\u6298\u53e0\u8fc7\u7a0b\u3002\u540c\u6837\uff0c\u5e02\u573a\u6570\u636e\u50cf\u94fe\u6761\uff0c\u6298\u53e0\u8d77\u6765\u663e\u793a\u72b6\u6001\u3002\u7a33\u5b9a\u72b6\u6001\u4e0b\uff0c\u5e02\u573a\u201c\u6298\u53e0\u201d\u590d\u6742\uff1b\u4e0d\u7a33\u5b9a\u65f6\uff0c\u201c\u5c55\u5f00\u201d\u7b80\u5355\u3002<\/p>\n\n\n
\n
\"\u86cb\u767d\u8d28\u6298\u53e0\u8f68\u8ff9\u56fe\"\/
\u56fe1\uff1a\u86cb\u767d\u8d28\u6298\u53e0\u8f68\u8ff9\u56fe\uff08\u6765\u6e90\uff1aNature\u6587\u7ae0\u300aProtein folding trajectories can be described quantitatively by…\u300b\uff09<\/figcaption><\/figure>\n<\/div>\n\n\n
\u73b0\u5728\u91cf\u5316\u4e3b\u6d41\u7684\u65b9\u6cd5\uff0c\u6bd4\u5982\u7528Wasserstein\u8ddd\u79bb\u505ak-means\u805a\u7c7b\uff0c\u5728\u5904\u7406\u4e00\u7ef4\u6570\u636e\u65f6\u8fd8\u884c\uff0c\u4f46\u4e00\u5230\u9ad8\u7ef4\u5c31\u5361\u58f3\u3002<\/p>\n\n\n\n
\u6253\u4e2a\u6bd4\u65b9\uff0c\u5c31\u50cf\u4f60\u770b\u4e00\u5f20\u7167\u7247\uff0c\u53ea\u76ef\u7740\u6bcf\u4e2a\u50cf\u7d20\u70b9\u7684\u4eae\u5ea6\uff0c\u5374\u5ffd\u7565\u4e86\u50cf\u7d20\u4e4b\u95f4\u7684\u5173\u7cfb\u3002\u8fd9\u6837\u7684\u5224\u65ad\u80af\u5b9a\u4e0d\u591f\u51c6\u3002<\/p>\n\n\n\n
\u65b9\u6cd5\u7c7b\u578b<\/th>\u5904\u7406\u4e00\u7ef4\u6570\u636e<\/th>\u5904\u7406\u9ad8\u7ef4\u6570\u636e<\/th>\u4fdd\u7559\u987a\u5e8f\u4fe1\u606f<\/th>\u8ba1\u7b97\u6548\u7387<\/th><\/tr><\/thead>
Wasserstein k-means<\/td>\u8868\u73b0\u4e0d\u9519<\/td>\u590d\u6742\u5ea6\u9ad8<\/td>\u4f1a\u4e22\u5931<\/td>\u9ad8\u7ef4\u65f6\u53d8\u6162<\/td><\/tr>
Market Folding\uff08\u65b0\u65b9\u6cd5\uff09<\/strong><\/td>\u5b8c\u5168\u6ca1\u95ee\u9898<\/td>\u7167\u6837\u641e\u5b9a<\/td>\u5b8c\u6574\u4fdd\u7559<\/strong><\/td>\u6838\u65b9\u6cd5\u66f4\u5feb<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\u6700\u5173\u952e\u7684\u662f\uff0c\u4f20\u7edf\u65b9\u6cd5\u5728\u5904\u7406\u5bf9\u6570\u6536\u76ca\u7387\u65f6\uff0c\u628a\u4ef7\u683c\u53d8\u5316\u7684\u5148\u540e\u987a\u5e8f\u7ed9\u5f04\u4e22\u4e86\u3002\u597d\u6bd4\u770b\u7535\u5f71\u53ea\u770b\u622a\u56fe\u4e0d\u770b\u5267\u60c5\uff0c\u5f88\u591a\u7ec6\u8282\u81ea\u7136\u5c31\u6f0f\u6389\u4e86\u3002<\/p>\n\n\n\n
\u4e8c\u3001\u8fdb\u4e00\u6b65\u7528\u51e0\u4f55\u89e3\u91ca<\/strong>\u5e02\u573a\u72b6\u6001<\/strong><\/h2>\n\n\n\n
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\u5173\u952e\u662f\u201c\u7ef4\u5ea6\u5d29\u584c\u201d\u3002\u4e0d\u7a33\u5b9a\u65f6\u6240\u6709\u6307\u6807\u9ad8\u5ea6\u76f8\u5173\uff0c\u5c31\u50cf\u6050\u614c\u4e2d\u5927\u5bb6\u4e00\u8d77\u5356\u3002\u76f8\u53cd\uff0c\u7a33\u5b9a\u65f6\u6307\u6807\u72ec\u7acb\uff0c\u5e02\u573a\u6709\u6d3b\u529b\u3002<\/p>\n\n\n\n
\u53e6\u4e00\u4e2a\u70b9\u662f\u201c\u7ed3\u6784\u5f20\u529b\u201d\u3002\u6307\u6807\u51b2\u7a81\u65f6\u72b6\u6001\u6613\u53d8\u3002\u5e02\u573a\u201c\u80fd\u91cf\u201d\u4f4e\u65f6\u7a33\u5b9a\uff0c\u9ad8\u65f6\u6613\u7834\u3002<\/p>\n\n\n\n
\u5e02\u573a\u72b6\u6001<\/th>\u7279\u5f81<\/th>\u4f8b\u5b50<\/th><\/tr>
\u6298\u53e0\uff08\u7a33\u5b9a\uff09<\/td>\u9ad8\u7ef4\u3001\u590d\u6742\u3001\u591a\u6837<\/td>\u8d8b\u52bf\u5e73\u7a33\u671f<\/td><\/tr>
\u5c55\u5f00\uff08\u4e0d\u7a33\u5b9a\uff09<\/td>\u4f4e\u7ef4\u3001\u7edf\u4e00\u3001\u76f8\u5173\u9ad8<\/td>\u5e02\u573a\u8f6c\u6298\u6216\u5d29\u76d8<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
\u6709\u8da3\u7684\u53cd\u8f6c\uff1a<\/strong>\u5065\u5eb7\u5e02\u573a\u662f\u201c\u4e71\u201d\u7684\uff0c\u9ad8\u4fe1\u606f\u590d\u6742\u5ea6\uff1b\u5371\u673a\u662f\u201c\u6709\u5e8f\u201d\u7684\uff0c\u4f4e\u590d\u6742\u5ea6\u3002\u8fd9\u98a0\u8986\u4e86\u76f4\u89c9\u3002<\/p>\n\n\n\n
\u4e09\u3001\u5e02\u573a\u6298\u53e0\u7684\u65b9\u6cd5<\/strong><\/h2>\n\n\n\n
\u90a3\u6211\u4eec\u5982\u4f55\u6765\u5b9e\u73b0\u54a7\uff1f\u5c31\u662f\u53ef\u4ee5\u501fAlphaFold\u7684\u601d\u8def\uff1a\u65f6\u95f4\u6570\u636e\u50cf\u6c28\u57fa\u9178\u5e8f\u5217\uff0c\u65f6\u95f4\u70b9\u95f4\u4e92\u52a8\u50cf\u6b8b\u57fa\u8054\u7cfb\u3002<\/p>\n\n\n\n
\u7528\u6570\u5b66\u5efa\u4e92\u52a8\u77e9\u9635\uff0c\u8ba1\u7b97\u4fe1\u606f\u590d\u6742\u5ea6\u3002\u590d\u6742\u5ea6\u9ad8\u4f46\u72b6\u6001\u7a33\u5b9a\u3002\u6b65\u9aa4\u7b80\u5355\uff1a<\/p>\n\n\n\n
    \n
  1. \u62ff\u8d44\u4ea7\u6570\u636e\u3002<\/li>\n\n\n\n
  2. \u90095\u4e2a\u5e38\u89c1\u6307\u6807\uff1a\u52a8\u91cf\u3001\u6ce2\u52a8\u8303\u56f4\u3001\u53c2\u4e0e\u5ea6\u3001\u7d2f\u79ef\u6d41\u3001\u8303\u56f4\u632f\u8361\u3002\u5f52\u4e00\u5316\u52300-1\u3002<\/li>\n\n\n\n
  3. \u752850\u671f\u7a97\u53e3\u3002<\/li>\n\n\n\n
  4. \u7b97\u7a97\u53e3\u5185\u76f8\u5173\u77e9\u9635\u3002<\/li>\n\n\n\n
  5. \u5206\u89e3\u7279\u5f81\u503c\uff0c\u5f52\u4e00\u5316\u3002<\/li>\n\n\n\n
  6. \u7b97\u4fe1\u606f\u590d\u6742\u5ea6\uff08\u7528scipy\u5e93\uff09\u3002<\/li>\n\n\n\n
  7. \u4e94\u671f\u5e73\u5747\uff0c\u5f97\u6298\u53e0\u5206\u6570\u3002<\/li>\n<\/ol>\n\n\n\n
    \u4ee3\u7801\u4f8b\u5b50\uff08Python\uff09\uff1a<\/strong><\/p>\n\n\n\n
    window_size = 50\nentropy_scores = []\n\nfor\u00a0i\u00a0in\u00a0range(len(df)):\n\u00a0 \u00a0\u00a0if\u00a0i < window_size:\n\u00a0 \u00a0 \u00a0 \u00a0 entropy_scores.append(np.nan)\n\u00a0 \u00a0 \u00a0 \u00a0\u00a0continue\n\n\u00a0 \u00a0 window =\u00a0df[features].iloc[i-window_size:i]\n\u00a0 \u00a0 corr_matrix = window.corr().fillna(0)\n\n\u00a0 \u00a0 eigenvalues, _ = np.linalg.eigh(corr_matrix)\n\u00a0 \u00a0 eigenvalues = np.abs(eigenvalues)\n\u00a0 \u00a0 eigenvalues = eigenvalues \/ eigenvalues.sum()\n\n\u00a0 \u00a0 H = entropy(eigenvalues, base=2)\n\u00a0 \u00a0 entropy_scores.append(H)\n\ndf['Market_Entropy'] = entropy_scores\ndf['Folding_Score'] =\u00a0df['Market_Entropy'].rolling(5).mean()<\/code><\/pre>\n\n\n\n
    \u8fd9\u4e2a\u5206\u6570\u50cf\u4f53\u6e29\u8ba1\uff1a\u9ad8\u8868\u793a\u6d3b\u529b\uff0c\u4f4e\u8868\u793a\u8b66\u62a5\u3002<\/p>\n\n\n
    \n
    \"\u5e02\u573a\u72b6\u6001\u68c0\u6d4b\u56fe\"\/
    \u56fe2\uff1a\u5e02\u573a\u72b6\u6001\u68c0\u6d4b\u793a\u4f8b\u56fe<\/figcaption><\/figure>\n<\/div>\n\n\n
    <\/p>\n\n\n\n
    \u56db\u3001\u5b9e\u9645\u6d4b\u8bd5\u548c\u7ed3\u679c<\/strong><\/h2>\n\n\n\n
    \u6211\u7528\u6bd4\u7279\u5e01\u548c\u80a1\u7968\u6570\u636e\u505a\u4e86\u4e9b\u6d4b\u8bd5\u3002\u6bd4\u7279\u5e012\u5e741\u5c0f\u65f6\u6570\u636e\uff1b\u80a1\u7968\u7528\u4e86\u82f9\u679c\u3001\u6807\u666e\u3002<\/p>\n\n\n\n
    \u9700\u8981\u4e0b\u9762\u6d4b\u8bd5\u7a0b\u5e8f\u5b8c\u6574\u4ee3\u7801\u7684\u53ef\u4ee5\u70b9\u51fbAI\u5ba2\u670d<\/strong><\/a>\u540e\u8f93\u5165\u3010\u5e02\u573a\u6298\u53e0<\/strong>\u3011\u83b7\u53d6\u3002<\/p>\n\n\n\n
    \u65b9\u6cd5\uff1a<\/strong>\u7528\u4e2d\u4f4d\u6570\u5206\u9ad8\u4f4e\u590d\u6742\u5ea6\u72b6\u6001\uff0c\u770b\u672a\u6765\u6ce2\u52a8\u3002<\/p>\n\n\n\n
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    \"\u56fe\u7247\"\/<\/figure>\n\n\n\n
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