metal-binding-prediction:通过氨基酸序列预测蛋白质中金属结合位点的方法

上传者: 42138780 | 上传时间: 2023-04-09 12:39:17 | 文件大小: 316.17MB | 文件类型: ZIP
蛋白质金属结合位点预测 投稿人:田秋,郑子涵,金文浩 生物学意义: 蛋白质及其结构是生命中生物学功能的关键。 通过翻译,核糖体将延长氨基酸序列链,这些氨基酸的物理化学特性及其相互依赖性使一级结构折叠成其复杂的三级结构。 一旦建立了结构,蛋白质结构可能会允许某些离子结合,这可能导致该结构通过构象变化更稳定,或有助于催化。 例如,锌指稳定结构,或血红素基团中离子的必要性,以使血红蛋白转运氧气。 另外,结合位点的序列和结构往往在整个世代中都被保守,并且来自蛋白质数据库(PDB)的大约1/3的蛋白质结构包含金属离子这一事实可能表明它显着干预了蛋白质的行为。 目标 : 我们的兴趣是利用一个突出的神经网络来识别哪些金属与哪个序列结合,以及该金属与哪些氨基酸特异性结合。 我们的目标是将金属分类为准确度为95%的序列。 我们的目标是对哪些氨基酸与F1分数达75%的金属结合进行分类。 概述: [

文件下载

资源详情

[{"title":"( 63 个子文件 316.17MB ) metal-binding-prediction:通过氨基酸序列预测蛋白质中金属结合位点的方法","children":[{"title":"metal-binding-prediction-master","children":[{"title":".gitignore <span style='color:#111;'> 1.13KB </span>","children":null,"spread":false},{"title":"Zihan","children":[{"title":"figs","children":[{"title":"Zihan_CNN_1.png <span style='color:#111;'> 7.09KB </span>","children":null,"spread":false},{"title":"Zihan_CNN_20.png <span style='color:#111;'> 7.61KB </span>","children":null,"spread":false}],"spread":true},{"title":"FOFE + CNN.ipynb <span style='color:#111;'> 122.60KB </span>","children":null,"spread":false},{"title":"Metal_all_20180116.snappy.parquet <span style='color:#111;'> 17.17MB </span>","children":null,"spread":false},{"title":"Main_type.ipynb <span style='color:#111;'> 37.10KB </span>","children":null,"spread":false},{"title":"Main.ipynb <span style='color:#111;'> 30.53KB </span>","children":null,"spread":false},{"title":"dictionaries","children":[{"title":"vocab_dict_fofe <span style='color:#111;'> 4.19KB </span>","children":null,"spread":false}],"spread":true},{"title":"fofe.py <span style='color:#111;'> 517B </span>","children":null,"spread":false},{"title":"main_cnn_fofe.ipynb <span style='color:#111;'> 39.69KB </span>","children":null,"spread":false},{"title":"modules.py <span style='color:#111;'> 16.88KB </span>","children":null,"spread":false},{"title":"2-gram FOFE.ipynb <span style='color:#111;'> 58.53KB </span>","children":null,"spread":false},{"title":"modules_type.py <span style='color:#111;'> 16.94KB </span>","children":null,"spread":false}],"spread":false},{"title":"Workflow_Chart.png <span style='color:#111;'> 174.21KB </span>","children":null,"spread":false},{"title":"predictor.py <span style='color:#111;'> 2.83KB </span>","children":null,"spread":false},{"title":"Tian","children":[{"title":"trainer_struct.png <span style='color:#111;'> 55.18KB </span>","children":null,"spread":false},{"title":"model_CBRNN.png <span style='color:#111;'> 40.69KB </span>","children":null,"spread":false},{"title":"flowchart.jpg <span style='color:#111;'> 77.96KB </span>","children":null,"spread":false},{"title":"main&modules","children":[{"title":"main_ver_2.ipynb <span style='color:#111;'> 12.04KB </span>","children":null,"spread":false},{"title":"modules_ver_2.ipynb <span style='color:#111;'> 17.24KB </span>","children":null,"spread":false},{"title":"Modules_ver_1.ipynb <span style='color:#111;'> 16.86KB </span>","children":null,"spread":false},{"title":"main_ver_3.ipynb <span style='color:#111;'> 13.22KB </span>","children":null,"spread":false},{"title":"modules_ver_3.ipynb <span style='color:#111;'> 19.18KB </span>","children":null,"spread":false},{"title":"main_ver_1.ipynb <span style='color:#111;'> 14.21KB </span>","children":null,"spread":false}],"spread":true},{"title":"model_BRNN.png <span style='color:#111;'> 24.20KB </span>","children":null,"spread":false},{"title":"flowchart.xml <span style='color:#111;'> 2.55KB </span>","children":null,"spread":false}],"spread":true},{"title":"datasets","children":[{"title":"Metal_all_20180116.snappy.parquet <span style='color:#111;'> 17.17MB </span>","children":null,"spread":false},{"title":"Metal_all_20180601.parquet <span style='color:#111;'> 17.02MB </span>","children":null,"spread":false},{"title":"Metal_all_20180601_predicted.parquet <span style='color:#111;'> 17.04MB </span>","children":null,"spread":false}],"spread":true},{"title":"models","children":[{"title":"NI.json <span style='color:#111;'> 4.08KB </span>","children":null,"spread":false},{"title":"ZN.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"CU.h5 <span style='color:#111;'> 53.64MB </span>","children":null,"spread":false},{"title":"CO.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"NI.h5 <span style='color:#111;'> 14.86MB </span>","children":null,"spread":false},{"title":"MG.h5 <span style='color:#111;'> 53.64MB </span>","children":null,"spread":false},{"title":"FE.h5 <span style='color:#111;'> 14.86MB </span>","children":null,"spread":false},{"title":"ZN.h5 <span style='color:#111;'> 14.86MB </span>","children":null,"spread":false},{"title":"MG.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"CA.h5 <span style='color:#111;'> 53.64MB </span>","children":null,"spread":false},{"title":"metal_predict.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"MN.h5 <span style='color:#111;'> 14.86MB </span>","children":null,"spread":false},{"title":"CO.h5 <span style='color:#111;'> 53.64MB </span>","children":null,"spread":false},{"title":"CA.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"MN.json <span style='color:#111;'> 4.10KB </span>","children":null,"spread":false},{"title":"CU.json <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"metal_predict.h5 <span style='color:#111;'> 175.45KB </span>","children":null,"spread":false},{"title":"FE.json <span style='color:#111;'> 4.10KB </span>","children":null,"spread":false}],"spread":false},{"title":"predictor.ipynb <span style='color:#111;'> 4.80KB </span>","children":null,"spread":false},{"title":"metal_prediction.ipynb <span style='color:#111;'> 9.81KB </span>","children":null,"spread":false},{"title":"dictionaries","children":[{"title":"seq_n_gram_to_vec_dict_w_UX <span style='color:#111;'> 16.24MB </span>","children":null,"spread":false},{"title":"metal_dict <span style='color:#111;'> 72B </span>","children":null,"spread":false},{"title":"vocab_dict_fofe <span style='color:#111;'> 4.19KB </span>","children":null,"spread":false},{"title":"seqs_dict_onehot <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false}],"spread":true},{"title":"README.md <span style='color:#111;'> 4.07KB </span>","children":null,"spread":false},{"title":"MBS_prediction.ipynb <span style='color:#111;'> 14.53KB </span>","children":null,"spread":false},{"title":"modules.py <span style='color:#111;'> 17.41KB </span>","children":null,"spread":false},{"title":"proteinSequenceEncoder.py <span style='color:#111;'> 3.47KB </span>","children":null,"spread":false},{"title":"Lowan","children":[{"title":"sample_AAproperty.xlsx <span style='color:#111;'> 10.24KB </span>","children":null,"spread":false},{"title":"AASA_NN.ipynb <span style='color:#111;'> 152.50KB </span>","children":null,"spread":false},{"title":"onehotCNN.py <span style='color:#111;'> 4.75KB </span>","children":null,"spread":false},{"title":"Metal_all_20180116.snappy.parquet <span style='color:#111;'> 17.17MB </span>","children":null,"spread":false}],"spread":true},{"title":"logs","children":[{"title":"results.txt <span style='color:#111;'> 2.48KB </span>","children":null,"spread":false},{"title":"results_sample.txt <span style='color:#111;'> 2.48KB </span>","children":null,"spread":false}],"spread":false}],"spread":false}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明