Hidden Markov models (HMMs) are statistical models that can be used to model systems with hidden states. HMMs assume the system is a Markov process where the probability of each state depends only on the previous state. HMMs have applications in DNA sequence analysis, protein family profiling, prediction of DNA functional sites, prediction of genes, and digital communications. Popular HMM-based tools include GENSCAN, GENMARK, and HMMgene. Both structural and functional annotation of genomes is important. Structural annotation identifies genomic elements like open reading frames and gene structure, while functional annotation attaches biological information like biochemical function. Functional annotation is important to understand large lists of genes/proteins. Gene ontology annotation is commonly used for

1. Hidden markov model (HMM)

2. Hidden markov model (HMM)
 A hidden markov model is a statistical model in which
the system is being modeled is assumed to be a markov
process with hidden states.
 Markov chain property: probability of each subsequent
state depends only on what was the previous state.

3. Hmm applications
 DNA sequence analysis
 Protein family profiling
 Predprediction
 Digital communications
 Prediction of DNA functional sites
 Prediction of genes

4. Hmm based tools
 GENSCAN
 GENMARK
 HMMgene

5. Genome annotation
 Biologists refer to both the annotation of the genome
and functional annotation of gene products:
 Structural annotation and
 Functional annotation

6. structural annotati0n
 Identification of
genomic elements.
 ORFs predicted during
genome assembly
 Location of ORFs
 Gene structure
 Coding regions
 Location of regulatory
motifs etc.,
Functional
annotation
 Attaching biological
information to genomics
elements.
 Biochemical function
 Biological function
 Involved regulation and
interactions
 Expression etc.,

7. Why functional annotation
 Enables you to take large “laundry lists” of
genes/proteins and turn them into a biologically useful
model

8. Functional annotation
 Annotation of gene products = gene ontology(GO)
annotation.
 Initially predicted ORFs have no functional literature
and GO annotation relies on computational methods(
rapid but ? Quantity vs quality)
 Functional literature exists for many genes/proteins
prior to genome sequencing (slow but provide high
quality annotation)

9. Types of functional
annotation
 Based in direct experimental evidence of function:
 Enzyme assays
 Binding experiments
 Pathway analysis
 Synthetic lethal
 Functional complementation
 Gene mutations

10.  Indirect evidence of functions
 Expression analysis
 Structure analysis
 Sequence analysis

11. Thank you