Alternative splice site recognition based on a new fuzzy support vector machine
نویسندگان
چکیده
منابع مشابه
Alternative splice site recognition based on a new fuzzy support vector machine.
Accurate alternative splice site (ASS) recognition is an important and difficult topic in the gene identification, and the average recognition rate is still ,85% [1]. Many statistical pattern recognition methods, such as neural networks (NNs) and support vector machine (SVM), were used for this task [2,3]. Among them, SVM can construct a good highdimensional learning model in the case of limite...
متن کاملNamed Entity Recognition Using a New Fuzzy Support Vector Machine
Recognizing and extracting exact name entities, like Persons, Locations, Organizations, Dates and Times are very useful to mining information from electronics resources and text. Learning to extract these types of data is called Named Entity Recognition (NER) task. Proper named entity recognition and extraction is important to solve most problems in hot research area such as Question Answering ...
متن کاملA Novel Splice Site Prediction Method using Support Vector Machine ?
We present a novel classification method for splice sites prediction using support vector machine (SVM). The method first represents input sequences by sequence-based features, including the information of the distribution of tri-nucleotides and the conserved features surrounding the splice sites characterized by Markov model. An F-score based feature selection method is then used to select inf...
متن کاملAcoustic detection of apple mealiness based on support vector machine
Mealiness degrades the quality of apples and plays an important role in fruit market. Therefore, the use of reliable and rapid sensing techniques for nondestructive measurement and sorting of fruits is necessary. In this study, the potential of acoustic signals of rolling apples on an inclined plate as a new technique for nondestructive detection of Red Delicious apple mealiness was investigate...
متن کاملNetwork Intrusion Detection Model based on Fuzzy Support Vector Machine
Network intrusion detection is of great importance in the research field of information security in computer networks. In this paper, we concentrate on how to automatically detect the network intrusion behavior utilizing fuzzy support vector machine. After analyzing the related works of the proposed paper, we introduce the main characterics of fuzzy support vector machine, and demonstrate its f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Biochimica et Biophysica Sinica
سال: 2013
ISSN: 1672-9145,1745-7270
DOI: 10.1093/abbs/gmt018