توسعه روابط ساختار-فعالیت تعمیم پذیر برای گیرنده های موسکارنیک استیل کولین با استفاده از روش های یادگیری ماشین و داده کاوی در پایگاه Binding-DB

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• نوع فایل: Word (.docx)
• رشته: شیمی
• گرایش مرتبط: شیمی تجزیه
• مقطع تحصیلی: کارشناسی ارشد
• عنوان: توسعه روابط ساختار-فعالیت تعمیم‌پذیر برای گیرنده‌های موسکارنیک استیل کولین با استفاده از روش‌های یادگیری ماشین و داده‌کاوی در پایگاه Binding-DB – فصل چهارم پایان‌نامه
• موضوع: ارائه و تحلیل نتایج حاصل از پردازش داده‌های Binding-DB، استخراج ویژگی‌های مولکولی، اجرای روش‌های کمومتریک و یادگیری ماشین و ارزیابی مدل‌های توسعه‌یافته برای پیش‌بینی روابط ساختار–فعالیت.
• محتوای فصل: در فصل چهارم، داده‌های استخراج‌شده از پایگاه Binding-DB پس از پاک‌سازی، استانداردسازی و پیش‌پردازش مورد تجزیه‌وتحلیل قرار می‌گیرند. ویژگی‌های مجموعه داده و توصیفگرهای مولکولی محاسبه و انتخاب شده و نتایج حاصل از روش‌های کاهش ابعاد و انتخاب ویژگی بررسی می‌شوند. سپس مدل‌های مختلف رگرسیون، طبقه‌بندی یا سایر الگوریتم‌های یادگیری ماشین مورد استفاده قرار گرفته و عملکرد آن‌ها با معیارهای آماری مناسب ارزیابی می‌شود. شاخص‌هایی مانند ضریب تعیین (R²)، RMSE، MAE و در مدل‌های طبقه‌بندی Accuracy، Precision، Recall، F1 و AUC، متناسب با روش پژوهش، گزارش و مقایسه می‌شوند. در نهایت، بهترین مدل از نظر دقت، پایداری و قابلیت تعمیم مشخص شده و عوامل مؤثر بر پیش‌بینی فعالیت ترکیبات تحلیل می‌شوند.
• محورهای اصلی: تحلیل داده‌های Binding-DB، کمومتریک، پیش‌پردازش داده، توصیفگرهای مولکولی، انتخاب ویژگی، یادگیری ماشین، مدل‌سازی QSAR، تحلیل آماری، رگرسیون، طبقه‌بندی، اعتبارسنجی، RMSE، MAE، R²، ارزیابی مدل
• حوزه تخصصی: شیمی تجزیه، کمومتریک و مدل‌سازی آماری داده‌های شیمیایی و زیستی
• جامعه مورد مطالعه: مجموعه ترکیبات و لیگاندهای ثبت‌شده در Binding-DB با داده‌های مربوط به اتصال به گیرنده‌های موسکارینیک استیل‌کولین
• فرمت: Word قابل ویرایش

• این مجموعه هیچ مسئولیتی در قبال متون نگارش شده ندارد.
• فایل صرفاً جهت کمک و تسهیل روند نگارش فصول می‌باشد و مسئولیت استفاده نهایی و صحت‌سنجی علمی بر عهده پژوهشگر است.

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