Genomics via Optical Mapping (I): 0-1 Laws for Mapping with Single Molecules

2013 ◽  
Author(s):  
Thomas Anantharaman ◽  
Bud (Bhubaneswar) Mishra

The genomic data that can be collected from a single DNA molecule by the best chemical and optical methods (e.g., using technologies from OpGen, BioNanoGenomics, NABSys, PacBio, etc.) are badly corrupted by many poorly understood noise processes. Thus, single molecule technology derives its utility through powerful probabilistic modeling, which can provide precise lower and upper bounds on various experimental parameters to create the correct map or validate sequence assembly. As an example, this analysis shows how as the number of "imaged" single molecules (i.e., coverage) is increased in the optical mapping data, the probability of successful computation of the map jumps from 0 to 1 for fairly small number of molecules.

eLife ◽  
2014 ◽  
Vol 3 ◽  
Author(s):  
Jordan Monnet ◽  
Terence R Strick

A fluorescent imaging technique called fastFISH has been used to track the various steps involved in the transcription of a single DNA molecule.


Author(s):  
Michel Orrit

This chapter gives an overview of the main optical methods used to detect and study single molecules and other small objects (nano-objects). Much of the work so far has exploited the excellent sensitivity and selectivity of fluorescence, but several new techniques, mostly based on nonlinear optics, have recently reached the single-molecule or single-nanoparticle regime. The chapter briefly discusses some results with reference to published reviews. Single-molecule techniques have now been incorporated into the arsenal of the physico-chemist and the cell biologist. However, the recent development of super-resolution techniques and of new labels suggests that further progress can be expected from measurements on single nano-objects in the next few years.


2021 ◽  
Author(s):  
Takanori Harashima ◽  
Yusuke Hasegawa ◽  
Satoshi Kaneko ◽  
Yuki Jono ◽  
Shintaro Fujii ◽  
...  

Hybridization of a single DNA molecule on a surface was investigated by electrical conductance measurements. The hybridization efficiency increases with increasing the DNA concentration, in contrast to preceding studies with ensemble studies.


2021 ◽  
Author(s):  
Robin Öz ◽  
Jing L Wang ◽  
Raphael Guerois ◽  
Gaurav Goyal ◽  
Sriram KK ◽  
...  

Abstract We use single-molecule techniques to characterize the dynamics of prokaryotic DNA repair by non-homologous end-joining (NHEJ), a system comprised only of the dimeric Ku and Ligase D (LigD). The Ku homodimer alone forms a ∼2 s synapsis between blunt DNA ends that is increased to ∼18 s upon addition of LigD, in a manner dependent on the C-terminal arms of Ku. The synapsis lifetime increases drastically for 4 nt complementary DNA overhangs, independently of the C-terminal arms of Ku. These observations are in contrast to human Ku, which is unable to bridge either of the two DNA substrates. We also demonstrate that bacterial Ku binds the DNA ends in a cooperative manner for synapsis initiation and remains stably bound at DNA junctions for several hours after ligation is completed, indicating that a system for removal of the proteins is active in vivo. Together these experiments shed light on the dynamics of bacterial NHEJ in DNA end recognition and processing. We speculate on the evolutionary similarities between bacterial and eukaryotic NHEJ and discuss how an increased understanding of bacterial NHEJ can open the door for future antibiotic therapies targeting this mechanism.


1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.


Author(s):  
S. Yahya Mohamed ◽  
A. Mohamed Ali

In this paper, the notion of energy extended to spherical fuzzy graph. The adjacency matrix of a spherical fuzzy graph is defined and we compute the energy of a spherical fuzzy graph as the sum of absolute values of eigenvalues of the adjacency matrix of the spherical fuzzy graph. Also, the lower and upper bounds for the energy of spherical fuzzy graphs are obtained.


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