انتخاب ویژگی و طبقه‌بندی سلول‌های سرطانی بر پایه داده‌های ریزآرایه با استفاده از الگوریتم جستجوی فاخته چندهدفه
الموضوعات :
خدیجه کمری
1
(دانشگاه هرمزگان)
فرزان رشیدی
2
(دانشگاه هرمزگان)
عبدالله خلیلی
3
(دانشگاه هرمزگان)
الکلمات المفتاحية: انتخاب ویژگیانتخاب نمونهداده‌کاویریزآرایهالگوریتم جستجوی فاخته چندهدفهخوشه‌بندی فازی,
ملخص المقالة :
داده‌هاي ریزآرایه نقش مؤثری در طبقه‌بندی و تشخیص انواع بافت‌های سرطانی ایفا می‌کنند. با این حال در پژوهش‌های مرتبط با سرطان، تعداد نسبتاً کم نمونه‌ها در مقایسه با تعداد بسیار زیاد ژن‌ها، باعث ایجاد مشکلاتی از قبیل کاهش کارایی طبقه‌بندها، افزایش هزینه‌های محاسباتی و پیچیدگی در طبقه‌بندی سلول‌های سرطانی خواهد شد. یک راهکار مناسب جهت افزایش کارایی طبقه‌بندها، حذف ژنهای نامربوط و انتخاب نمونه‌های مناسب برای آموزش طبقه‌بندها است. در این مقاله یک مدل ترکیبی بر پایه الگوریتم بهینه‌سازی جستجوی فاخته چندهدفه و خوشه‌بندی فازی برای طبقه‌بندی داده‌های ریزآرایه پیشنهاد شده است. در اين مطالعه از نسخه دودویی الگوريتم جستجوی فاخته چندهدفه به منظور انتخاب ويژگي‌هاي مرتبط با بیماری و از نسخه پیوسته آن برای انتخاب تعداد نمونه‌های مناسب برای آموزش طبقه‌بندها استفاده شده است. به منظور تسریع در فرایند بهینه‌سازی و جلوگیری از گیرافتادن الگوریتم در بهینه‌های محلی، راهکارهای ابتکاری جدیدی نیز به الگوریتم اضافه شده‌اند. برای بررسی عملکرد مدل پیشنهادی، شبیه‌سازی‌های متعددی بر روی شش مجموعه داده سرطانی انجام گرفته و نتایج آن با دیگر مقالات مقایسه شده است. نتایج به دست آمده نشان می‌دهند در بسیاری از موارد مدل پیشنهادی قادر است در مقایسه با سایر روش‌ها، با انتخاب مجموعه کوچک‌تری از ژنهای متمایز، منجر به افزایش کارایی طبقه‌بندها شود.
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