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 دوم پایان‌نامه
• موضوع: بررسی مبانی نظری مربوط به داده‌کاوی و یادگیری ماشین در شیمی تجزیه، تحلیل داده‌های زیستی و مولکولی، روابط ساختار–فعالیت و استفاده از داده‌های پایگاه Binding-DB برای توسعه مدل‌های پیش‌بینی.
• محتوای فصل: در فصل دوم، مبانی نظری پژوهش شامل معرفی گیرنده‌های موسکارینیک استیل‌کولین، ویژگی‌های ساختاری و عملکردی آن‌ها و اهمیت بررسی برهم‌کنش لیگاند–گیرنده ارائه می‌شود. سپس مفاهیم روابط ساختار–فعالیت و مدل‌سازی کمی، روش‌های جمع‌آوری و آماده‌سازی داده‌های شیمیایی و زیستی و ویژگی‌های پایگاه Binding-DB بررسی می‌شوند. در ادامه، مبانی کمومتریک، داده‌کاوی و یادگیری ماشین در شیمی تجزیه، انواع توصیفگرهای مولکولی، انتخاب و استخراج ویژگی، پیش‌پردازش داده‌ها، کاهش ابعاد و روش‌های رگرسیون و طبقه‌بندی معرفی می‌شوند. همچنین مطالعات پیشین مرتبط با کاربرد روش‌های آماری و یادگیری ماشین در تحلیل داده‌های شیمیایی و توسعه مدل‌های ساختار–فعالیت بررسی خواهد شد.
• محورهای اصلی: شیمی تجزیه، کمومتریک، داده‌کاوی، یادگیری ماشین، Binding-DB، روابط ساختار–فعالیت، QSAR، توصیفگرهای مولکولی، پردازش داده، انتخاب ویژگی، مدل‌سازی آماری، گیرنده‌های موسکارینیک، استیل‌کولین
• حوزه تخصصی: شیمی تجزیه و کمومتریک، تحلیل داده‌های شیمیایی و زیستی و مدل‌سازی آماری
• جامعه مورد مطالعه: ترکیبات و لیگاندهای دارای داده‌های اتصال به گیرنده‌های موسکارینیک استیل‌کولین در پایگاه Binding-DB
• فرمت: Word قابل ویرایش

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