Understanding Bioinformatics

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A01=Jeremy O. Baum
A01=Marketa Zvelebil
AACC
advanced bioinformatics methods for researchers
algorithm
alpha helix
amino acid
analysis
annealing
annotation
Author_Jeremy O. Baum
Author_Marketa Zvelebil
bacteria
bayesian method
Bayesian statistical modelling
beta sheet
biclustering
binding site
bioinformatics
biological database management
bistable switch
BLAST
branch-and-bound method
CAFASP
Cantor model
Category=PS
Category=UY
CE method
chaining
clustering
Coiled Coil
Coiled-coil structure
COILS
computational biology
conformation
conserved region
data classification
database
derived data
DIALIGN
dicodon
discriminants
DNA microarray
DNA Sequence
DNA structure
docking
dot-plot
EcoParse
eMOTIF
energy
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_science
euclidean distance
eukaryote
evolution
exon
Fitch-Margoliash method
flat-file database
force field
function optimization
Gamma distance correction
gap
Gap Penalties
gene control
gene detection
gene prediction
gene structure
GeneMark
GeneSplicer
genome annotation techniques
GenScan
Gibbs
GLIMMER
GOR method
gradual sequence addition
hashing
hidden Markov model
hierarchical cluster analysis
HMM
homology
Homology Modeling
indexing
interaction site
intron
Jukes
kinase
leucine zipper
ligand
Local Alignments
long-branch attraction problem
low-complexity region
mahalanobis distance
mass spectrometry
microarray database
modularity
molecular biology
molecular clock
molecular data analysis
molecular dynamics
molecular evolution
Multiple Alignment
Multiple Sequence Alignment
mutation
nearest-neighbor method
Needleman-Wunsch
neighbor-joining method
NetPlantGene
neural network
nonparametric test
nonredundancy
nucleic acid
ontology
ORPHEUS
orthologous gene
Output Layer Units
p-distance
pairwise sequence alignment
pearson correlation coefficient
percentage identity
Pfam
phylogenetic tree
phylogeny
PI3 Kinase P110a
Poisson distance correction
polypeptide
Position Specific Scoring Matrices
position-specific matrix
potentials
prediction
primary data
primary structure
principal component analysis
probability
promoter region
protein
protein folding
protein folding prediction
protein interaction database
protein microarray
protein sequence motif
protein structure
proteomics
Q3
quantitative biology
quartet-puzzling methid
Query Sequence
reading frame
recombination
redundancy
relational database
residue propensity
Residue Types
ribosome binding
RNA polymerase
RNA structure
robustness
scoring
secondary structure
Secondary Structure Prediction
Secondary Structure Prediction Methods
self-organizing tree algorithm
sequence alignment
sequence analysis
sequence database
sequence pattern
sequence realignment
serial analysis of gene expression
SH2 Domain
small ribosomal subunit RNA sequence
SOTA
sov value
Spice site
splice site
star-decomposition method
statistics
stepwise addition
structural biology
structural database
structure comparison
substitution alignment
substitution matrix
suffix tree
support vector machine
systems biology
systems biology integration
tertiary structure
thermodynamic simulation
threading
transcription
translation
Transmembrane Helix
tree topology
tRNA scan
UPGMA method
vector alignment search tool
visualization
XML

Product details

  • ISBN 9780815340249
  • Weight: 2120g
  • Dimensions: 219 x 276mm
  • Publication Date: 06 Sep 2007
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Suitable for advanced undergraduates and postgraduates, Understanding Bioinformatics provides a definitive guide to this vibrant and evolving discipline. The book takes a conceptual approach. It guides the reader from first principles through to an understanding of the computational techniques and the key algorithms. Understanding Bioinformatics is an invaluable companion for students from their first encounter with the subject through to more advanced studies.

The book is divided into seven parts, with the opening part introducing the basics of nucleic acids, proteins and databases. Subsequent parts are divided into 'Applications' and 'Theory' Chapters, allowing readers to focus their attention effectively. In each section, the Applications Chapter provides a fast and straightforward route to understanding the main concepts and 'getting started'. Each of these is then followed by Theory Chapters which give greater detail and present the underlying mathematics. In Part 2, Sequence Alignments, the Applications Chapter shows the reader how to get started on producing and analyzing sequence alignments, and using sequences for database searching, while the next two chapters look closely at the more advanced techniques and the mathematical algorithms involved. Part 3 covers evolutionary processes and shows how bioinformatics can be used to help build phylogenetic trees. Part 4 looks at the characteristics of whole genomes. In Parts 5 and 6 the focus turns to secondary and tertiary structure – predicting structural conformation and analysing structure-function relationships. The last part surveys methods of analyzing data from a set of genes or proteins of an organism and is rounded off with an overview of systems biology.

The writing style of Understanding Bioinformatics is notable for its clarity, while the extensive, full-color artwork has been designed to present the key concepts with simplicity and consistency. Each chapter uses mind-maps and flow diagrams to give an overview of the conceptual links within each topic.


Marketa Zvelebil

is the team leader of cancer informatics at The Breakthrough Toby Robins Breast Cancer Research Centre.

Jeremy O. Baum

is an Honorary Teaching Fellow in the School of Crystallography, Birkbeck College.

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