RVDB-prot, a reference viral protein database and its HMM profiles

We present RVDB-prot, a database corresponding to the protein equivalent of the nucleic acid reference virus database RVDB. Protein databases can be helpful to perform more sensitive protein sequence comparisons. Similarly to its homologous public repository, RVDB-prot aims to provide reliable and accurately annotated unique entries, while including also an Hidden Markov Model (HMM) protein profiles database for distant protein searching.

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RVDB-prot, a reference viral protein database and its HMM profiles

F1000Research ◽

10.12688/f1000research.18776.2 ◽

2020 ◽

Vol 8 ◽

pp. 530 ◽

Cited By ~ 1

Author(s):

Thomas Bigot ◽

Sarah Temmam ◽

Philippe Pérot ◽

Marc Eloit

Keyword(s):

Nucleic Acid ◽

Markov Model ◽

Protein Sequence ◽

Hidden Markov ◽

Protein Profiles ◽

Public Repository ◽

Protein Database ◽

Sequence Comparisons ◽

Protein Databases ◽

Reference Virus

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A new Hidden Markov Model for protein Quality Assessment using compatibility between protein sequence and structure

Tsinghua Science & Technology ◽

10.1109/tst.2014.6961026 ◽

2014 ◽

Vol 19 (6) ◽

pp. 559-567 ◽

Cited By ~ 2

Author(s):

Zhiquan He ◽

Wenji Ma ◽

Jingfen Zhang ◽

Dong Xu

Keyword(s):

Markov Model ◽

Hidden Markov Model ◽

Quality Assessment ◽

Protein Sequence ◽

Protein Quality ◽

Hidden Markov

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A Hidden Markov Model Approach to Model Protein Sequence and Structural Information: Identification of Helix-Turn-Helix DNA-Binding Motif

2006 IEEE International Conference on Granular Computing ◽

10.1109/grc.2006.1635821 ◽

2006 ◽

Author(s):

Changhui Yan

Keyword(s):

Dna Binding ◽

Markov Model ◽

Hidden Markov Model ◽

Protein Sequence ◽

Structural Information ◽

Hidden Markov ◽

Binding Motif ◽

Model Protein ◽

Model Approach

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Formalization of Hidden Markov Model

Formalized Probability Theory and Applications Using Theorem Proving ◽

10.4018/978-1-4666-8315-0.ch008 ◽

2015 ◽

pp. 116-128

Keyword(s):

Nucleic Acid ◽

Markov Model ◽

Hidden Markov Model ◽

Formal Verification ◽

Hidden Markov Models ◽

Markov Models ◽

Hidden Markov ◽

Formal Analysis ◽

The Core ◽

State Sequence

In this chapter, the authors provide the formalization of extended DTMC models, namely Hidden Markov Models (HMMs), which are the core concept for formally evaluating the probability of the occurrence of a particular observed sequence and finding the best state sequence to generate given observation (Mantyla & Tutkimuskeskus, 2001; Rabiner, 1990). In order to present the usefulness of the formalization of HMM and the formal verification of HMM properties, the authors illustrate the formal analysis of a DNA (Deoxyribon Nucleic Acid) sequence at the end of the chapter.

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