T-cell epitope vaccine design by immunoinformatics
A Patronov, I Doytchinova - Open biology, 2013 - royalsocietypublishing.org
Vaccination is generally considered to be the most effective method of preventing infectious
diseases. All vaccinations work by presenting a foreign antigen to the immune system in …
diseases. All vaccinations work by presenting a foreign antigen to the immune system in …
[HTML][HTML] Recent advances in developing web-servers for predicting protein attributes
KC Chou, HB Shen - Natural science, 2009 - scirp.org
Recent advance in large-scale genome se-quencing has generated a huge volume of pro-
tein sequences. In order to timely utilize the in-formation hidden in these newly discovered …
tein sequences. In order to timely utilize the in-formation hidden in these newly discovered …
DeepDTAF: a deep learning method to predict protein–ligand binding affinity
Biomolecular recognition between ligand and protein plays an essential role in drug
discovery and development. However, it is extremely time and resource consuming to …
discovery and development. However, it is extremely time and resource consuming to …
Minimum redundancy feature selection from microarray gene expression data
How to selecting a small subset out of the thousands of genes in microarray data is
important for accurate classification of phenotypes. Widely used methods typically rank …
important for accurate classification of phenotypes. Widely used methods typically rank …
Predicting protein–protein interactions based only on sequences information
J Shen, J Zhang, X Luo, W Zhu, K Yu… - Proceedings of the …, 2007 - National Acad Sciences
Protein–protein interactions (PPIs) are central to most biological processes. Although efforts
have been devoted to the development of methodology for predicting PPIs and protein …
have been devoted to the development of methodology for predicting PPIs and protein …
The spectrum kernel: A string kernel for SVM protein classification
We introduce a new sequence-similarity kernel, the spectrum kernel, for use with support
vector machines (SVMs) in a discriminative approach to the protein classification problem …
vector machines (SVMs) in a discriminative approach to the protein classification problem …
[图书][B] Kernel methods in computational biology
A detailed overview of current research in kernel methods and their application to
computational biology. Modern machine learning techniques are proving to be extremely …
computational biology. Modern machine learning techniques are proving to be extremely …
Comparing two K-category assignments by a K-category correlation coefficient
J Gorodkin - Computational biology and chemistry, 2004 - Elsevier
Predicted assignments of biological sequences are often evaluated by Matthews correlation
coefficient. However, Matthews correlation coefficient applies only to cases where the …
coefficient. However, Matthews correlation coefficient applies only to cases where the …
SVM-Prot: web-based support vector machine software for functional classification of a protein from its primary sequence
Prediction of protein function is of significance in studying biological processes. One
approach for function prediction is to classify a protein into functional family. Support vector …
approach for function prediction is to classify a protein into functional family. Support vector …
On prediction using variable order Markov models
R Begleiter, R El-Yaniv, G Yona - Journal of Artificial Intelligence Research, 2004 - jair.org
This paper is concerned with algorithms for prediction of discrete sequences over a finite
alphabet, using variable order Markov models. The class of such algorithms is large and in …
alphabet, using variable order Markov models. The class of such algorithms is large and in …