Motifs in Bioinformatics

Dr Sajith Ahamed
Assistant Professor
Department of Microbiology
HKRH College
Subject Name – 
Bioinformatics
Subject Code –
17UMBE51
Semester : V
Programme : B.Sc.Microbiology 
Moti
f
s
Defined 
as a
 
nucleotide 
or amino acid 
 
sequence 
pattern 
that 
is 
widespread 
and is
associated 
with a
 
biological
 
function
.
A 
sequence 
motif = A 
structural
 
Motif.
A 
sequence 
motif 
residing 
in the 
coding region 
 
may 
encode 
a 
structural
 
motif
.
Non-coding nucleotide motifs 
may 
have 
regulatory  
role. May 
have 
recognition sites 
for
DNA 
binding  proteins.
Motifs, 
profiles 
and 
patterns
Conserved region 
of a DNA or 
protein 
 
Motif
Qualitative expression 
of 
a motif –
 
Pattern
Regular
 
Expression
C[TA]TTG{X}
Quantitative expression 
of 
a motif –
 
Profile
Position 
Specific Scoring Matrices
 
(PSSMs)
Weight
 
matrices
Motifs/Patterns
N{P}[ST]{P}
[FILV]Qxxx[RK]Gxxx[RK]xx[FILVWY]
[] -> 
or 
(Probability 
information 
is
 
lost)
{} 
->
 
Not
() 
->
 
repeated
^ -> 
Beginning
De 
novo 
prediction 
of
 
Motifs
MEME; 
EXTREME; AlignAce, Amadeus,  CisModule, FIRE, Gibbs 
Motif
Sampler,  
PhyloGibbs,
 
SeSiMCMC
,
 
ChIPMunk
 
and  
Weeder.
 
SCOPE
,
MotifVoter, 
and
 
Mprofiler
MEME 
(Multiple 
Expectation 
Maximization 
for  
Motif
 
Elicitation)
MacIsaac 
KD, Fraenkel 
E 
(2006) Practical Strategies 
for 
Discovering 
Regulatory 
DNA 
Sequence Motifs. 
PLoS 
Comput Biol 
2(4): e36.
doi:10.1371/journal.pcbi.0020036
http://journals.plos.org/ploscompbiol/article?id=info:doi/10.1371/journal.pcbi.0020036
MRLSFVPLLQLSRLVVSTQHSTKMSTVYRTCKMNEIALSLLAPTQPLDADQGVMSPMASSDQ
TTSIGDFRFLRTHHDKEERGLLVTSLTKGLAETSFPYR
 
YTSMCATICSITHSRADAAPAKQAH
P
r
osi
t
e
ATGCGTCTCTCCTTCGTTCCACTACTGCAGCTCTCTCGTCTGGTCGTTAGCACACAACATAGTACGAAAATGA
GCACAGTATACCGTACCTGCAAAATGAATGAAATAGCTCTCTCGTTGCTGGCGCCAACGCAGCCATTGGACG
CTGACCAGGGTGTTATGTCACCGATGGCCTCATCAGACCAGACAACCTCAATTGG TGACTTTCGGTTCCTGA
GAACCCACCACGATAAAGAAGAGCGGGGCTTGCTGGTTACCAGCCTCACAAAAGGTTTGGCTGAAACATCAT
TTCCGTATCGATACACTTCGATGTGCGCAACTATTTGTTCAATTACGCATTCTCGGGCAGATGCTGCGCCTGC  GAAGCAGGCGCACTA
Scan 
this sequence 
and 
get 
me the
 
motif
OR Build 
a
 
PSSM
A
T
GCGTCTCTC  A
T
GCCTC
T
G
T
C
A
T
GCGTCTCTC  A
T
GCGTCTCTC
A
T
GCGTCTA
T
C
Slide Note
Embed
Share

Bioinformatics studies the patterns of sequences called motifs, which play significant roles in biological functions. Conserving information from DNA or proteins, motifs can be predicted de novo using various tools and strategies. Exploring these motifs aids in understanding regulatory elements and functional regions within biological sequences.

  • Bioinformatics
  • Motifs
  • Sequence Patterns
  • De Novo Prediction
  • Regulatory Elements

Uploaded on Sep 26, 2024 | 0 Views


Download Presentation

Please find below an Image/Link to download the presentation.

The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. Download presentation by click this link. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.

E N D

Presentation Transcript


  1. Subject Name Subject Code Semester : V Programme : Subject Name Bioinformatics Subject Code 17UMBE51 Semester : V Programme : B.Sc.Microbiology Bioinformatics 17UMBE51 B.Sc.Microbiology Dr Sajith Ahamed Assistant Professor Department of Microbiology HKRH College

  2. Motifs Defined as a nucleotide or amino acid sequence pattern that is widespread and is associated with a biological function. A sequence motif = A structural Motif. A sequence motif residing in the coding region may encode a structural motif. Non-coding nucleotide motifs may have regulatory role. May have recognition sites for DNA binding proteins.

  3. Motifs, profiles and patterns C[TA]TTG{X} C T T T G X Conserved region of a DNA or protein Motif Qualitative expression of a motif Pattern Regular Expression C[TA]TTG{X} C A T T G X [TA] C T T G any Quantitative expression of a motif Profile Position Specific Scoring Matrices (PSSMs) Weightmatrices

  4. Motifs/Patterns N{P}[ST]{P} [FILV]Qxxx[RK]Gxxx[RK]xx[FILVWY] [] -> or (Probability information is lost) {} -> Not () -> repeated ^ -> Beginning

  5. De novo prediction of Motifs MEME; EXTREME; AlignAce, Amadeus, CisModule, FIRE, Gibbs Motif Sampler, PhyloGibbs, SeSiMCMC, ChIPMunk and Weeder.SCOPE, MotifVoter, and Mprofiler MEME (Multiple Expectation Maximization for Motif Elicitation)

  6. MacIsaac KD, Fraenkel E (2006) Practical Strategies for Discovering Regulatory DNA Sequence Motifs. PLoS Comput Biol 2(4): e36. doi:10.1371/journal.pcbi.0020036 http://journals.plos.org/ploscompbiol/article?id=info:doi/10.1371/journal.pcbi.0020036

  7. MRLSFVPLLQLSRLVVSTQHSTKMSTVYRTCKMNEIALSLLAPTQPLDADQGVMSPMASSDQMRLSFVPLLQLSRLVVSTQHSTKMSTVYRTCKMNEIALSLLAPTQPLDADQGVMSPMASSDQ TTSIGDFRFLRTHHDKEERGLLVTSLTKGLAETSFPYR YTSMCATICSITHSRADAAPAKQAH

  8. Prosite

  9. Scan this sequence and get me the motif ATGCGTCTCTCCTTCGTTCCACTACTGCAGCTCTCTCGTCTGGTCGTTAGCACACAACATAGTACGAAAATGA GCACAGTATACCGTACCTGCAAAATGAATGAAATAGCTCTCTCGTTGCTGGCGCCAACGCAGCCATTGGACG CTGACCAGGGTGTTATGTCACCGATGGCCTCATCAGACCAGACAACCTCAATTGG GAACCCACCACGATAAAGAAGAGCGGGGCTTGCTGGTTACCAGCCTCACAAAAGGTTTGGCTGAAACATCAT TTCCGTATCGATACACTTCGATGTGCGCAACTATTTGTTCAATTACGCATTCTCGGGCAGATGCTGCGCCTGC GAAGCAGGCGCACTA TGACTTTCGGTTCCTGA OR Build aPSSM ATGCGTCTCTC ATGCGTCTCTC ATGCGTCTATC ATGCCTCTGTC ATGCGTCTCTC

More Related Content

giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#giItT1WQy@!-/#