Motif Detection
Motif Detection - Related Videos
07:55
Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
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Cited by 3 •
2011
A straight-forward and robust method to identify potential regulatory motifs in co-regulated genes is presented. SCOPE does not require any user parameters and returns motifs that represent excellent candidates for regulatory signals. The identification of such regulatory signals helps to understand the underlying biology.
14:28
Peptide-based Identification of Functional Motifs and their Binding Partners
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Cited by 2 •
2013
Techniques to dissect the mechanisms underlying the secretion of HIV-1 Nef in exosomes are described. Specific short peptides derived from Nef and protein transfection were exploited to determine the structure, function, and binding partners of Nef’s Secretion Modification Region. These procedures have general relevance in many mechanistic studies.
03:41
Fluorescence Anisotropy-Based Detection of Protein-Protein Interactions
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2025
In this video, we describe the fluorescence anisotropy technique to study the interactions between the fluorophore-tagged Shwachman-diamond syndrome (SBDS) protein and the elongation factor-like 1 GTPase (EFL1). On incubating SBDS proteins with gradually increasing concentrations of EFL1, a steady increase in anisotropy is observed, indicating a successful interaction between the two proteins.
08:16
Identifying Caspases and their Motifs that Cleave Proteins During Influenza A Virus Infection
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Cited by 6 •
2022
Influenza A virus (IAV) infection activates the caspases that cleave host and viral proteins, which, in turn, have pro- and antiviral functions. By employing inhibitors, RNA interference, site-directed mutagenesis, and western blotting and RT-qPCR techniques, caspases in infected mammalian cells that cleave host cortactin and histone deacetylases were identified.
09:32
Stable DNA Motifs, 1D and 2D Nanostructures Constructed from Small Circular DNA Molecules
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Cited by 6 •
2019
This article presents a detailed protocol for T4 ligation and denaturing PAGE purification of small circular DNA molecules, annealing and native PAGE analysis of circular tiles, assembling and AFM imaging of 1D and 2D DNA nanostructures, as well as agarose gel electrophoresis and centrifugation purification of finite DNA nanostructures.
FAQs
A position-specific scoring matrix assigns different weights to nucleotides or amino acids at each position in a candidate pattern, rather than treating every position as equally informative. These weights reflect sequence preferences observed in an alignment. Scanning with the matrix therefore prioritizes matches that resemble the conserved arrangement while allowing tolerated variation within the motif.
Probabilistic models evaluate how likely a sequence pattern is to represent a motif rather than a random arrangement of residues. They can accommodate variation across positions and provide a basis for comparing candidate matches. This is useful when biologically related sequences are not identical, although the resulting predictions still require contextual assessment and, when possible, experimental validation.
Short patterns contain limited sequence information, so similar arrangements may appear by chance in DNA, RNA, or protein sequences. A computational match alone therefore does not establish biological significance. Conservation analysis provides supporting evidence by asking whether the pattern persists across related sequences, while experimental validation can test whether the predicted site or region has the proposed function.
An alignment places related DNA, RNA, or protein sequences in corresponding positions, making recurring residues or nucleotides easier to recognize. Conserved positions can then inform a position-specific scoring matrix or another probabilistic model. This connection helps distinguish patterns associated with shared biological roles from isolated matches that lack evidence of conservation or functional relevance.
A typical workflow begins with DNA, RNA, or protein sequences and examines them using sequence alignments, position-specific scoring matrices, or probabilistic models. The resulting candidate matches are then assessed through conservation analysis and interpreted in their biological context. Experimental validation may follow to determine whether a predicted pattern actually contributes to the proposed regulatory or functional role.
Motif detection can help locate transcription factor binding sites, predict protein domains, annotate genes, and examine regulatory networks. The appropriate interpretation depends on the molecule and the surrounding sequence evidence. For example, a candidate pattern in a regulatory region may support investigation of gene control, whereas a recurring protein sequence pattern may assist functional annotation.
Researchers should treat a predicted match as a candidate result rather than definitive evidence. They can compare its conservation across related sequences and consider whether the pattern fits the expected biological context. Because chance matches are possible, experimental validation remains important when establishing a regulatory role, protein function, gene annotation, or relationship within a biological network.