Hidden Markov models of biological primary sequence information.
نویسندگان
چکیده
منابع مشابه
Hidden Markov models of biological primary sequence information.
Hidden Markov model (HMM) techniques are used to model families of biological sequences. A smooth and convergent algorithm is introduced to iteratively adapt the transition and emission parameters of the models from the examples in a given family. The HMM approach is applied to three protein families: globins, immunoglobulins, and kinases. In all cases, the models derived capture the important ...
متن کاملStructural Information and Hidden Markov Models for Biological Sequence Analysis
Bioinformatics is a fast-developing field, which makes use of computational methods to analyse and structure biological data. An important branch of bioinformatics is structure and function prediction of proteins, which is often based on finding relationships to already characterized proteins. It is known that two proteins with very similar sequences also share the same 3D structure. However, t...
متن کاملHidden Markov models in biological sequence
The vast increase of data in biology has meant that many aspects of computational science have been drawn into the field. Two areas of crucial importance are large-scale data management and machine learning. The field between computational science and biology is varyingly described as “computational biology” or “bioinformatics.” This paper reviews machine learning techniques based on the use of...
متن کاملPropositionalisation of Profile Hidden Markov Models for Biological Sequence Analysis
Hidden Markov Models are a widely used generative model for analysing sequence data. A variant, Profile Hidden Markov Models are a special case used in Bioinformatics to represent, for example, protein families. In this paper we introduce a simple propositionalisation method for Profile Hidden Markov Models. The method allows the use of PHMMs discriminatively in a classification task. Previousl...
متن کاملHidden Markov Models and their Applications in Biological Sequence Analysis
Hidden Markov models (HMMs) have been extensively used in biological sequence analysis. In this paper, we give a tutorial review of HMMs and their applications in a variety of problems in molecular biology. We especially focus on three types of HMMs: the profile-HMMs, pair-HMMs, and context-sensitive HMMs. We show how these HMMs can be used to solve various sequence analysis problems, such as p...
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: Proceedings of the National Academy of Sciences
سال: 1994
ISSN: 0027-8424,1091-6490
DOI: 10.1073/pnas.91.3.1059