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HMMs

A Hidden Markov Model (HMM) is a general probabilistic model for sequences of symbols. In a Markov chain, the probability of each symbol depends only on the preceding one. Hidden Markov models are widely used in bioinformatics, most notably to replace sequence profile in the calculation of sequence alignments. [Pg.584]

Huxley suggested that crossbridges can move out in this way and bind to actin because S-2 of HMM acted as a flexible link between LMM in the thick filament backbone and S-1. This was based on the observation that heavy meromyosin could be digested by chymotrypsin into two further subffagments (Lowey et al., 1966), S-1 and S-2, as described above, and that S-1 contained the ATPase and actin binding sites, whereas S-2 did not moreover, S-2 did not self-aggregate, as did the rod or LMM portion of myosin. [Pg.216]

Figure 13, A schematic diagram of the motility assay. Myosin molecules (HMM or S-1 are also used) stick to glass coverslips coated with nitrocellulose. Actin, in solution, is then added to the glass coverslip and it binds to the myosin molecules. When ATP is added, actin can move over the surface, propelled by the myosin molecules. Figure 13, A schematic diagram of the motility assay. Myosin molecules (HMM or S-1 are also used) stick to glass coverslips coated with nitrocellulose. Actin, in solution, is then added to the glass coverslip and it binds to the myosin molecules. When ATP is added, actin can move over the surface, propelled by the myosin molecules.
Heavy meromyosin (HMM molecular mass about 340 kDa) is a soluble protein that has both a fibrous portion and a globular portion (Figure 49-4). It exhibits ATPase activity and binds to F-actin. Digestion of HMM with papain generates two subfragments, S-1 and S-2. The S-2 fragment is fibrous in character, has no ATPase activity, and does not bind to F-actin. [Pg.561]

S-1 (molecular mass approximately 115 kDa) does exhibit ATPase activity, binds L chains, and in the absence of ATP will bind to and decorate actin with arrowheads (Figure 49-5). Both S-1 and HMM exhibit ATPase activity, which is accelerated 100- to 200-fold by complexing with F-actin. As discussed below, F-actin greatly enhances the rate at which myosin ATPase releases its products, ADP and Pj. Thus, although F-actin does not affect the hydrolysis step per se, its ability to promote release of the products produced by the ATPase activity greatly accelerates the overall rate of catalysis. [Pg.561]

Similarly, monometallic Rh, Pd, and Au and bimetallic Pt-Rh and Pt-Pd nanowires were prepared in FSM-16 or HMM-1 by the photoreduction method [30,33,34]. The bimetallic wires gave lattice fringes in the HRTEM images, and the EDX analysis indicated the homogeneous composition of the two metals. These results show that the wires are alloys of Pt-Rh and Pt-Pd. Mesoporous silica films were also used as a template for the synthesis of uniform metal particles and wires in the channels [35,36]. Recently, highly ordered Pt nanodot arrays were synthesized in a mesoporous silica thin film with cubic symmetry by the photoreduction method [37]. The... [Pg.385]

Figure 7. STM images of Pt wires extracted from Et-HMM-1 (a), FSM-16 (b), and Ph-HMM-1 (c). Pt wires were extracted with HF and deposited on HOPG. (Adapted from Ref. [32], 2006, with permission from American Chemical Society.)... Figure 7. STM images of Pt wires extracted from Et-HMM-1 (a), FSM-16 (b), and Ph-HMM-1 (c). Pt wires were extracted with HF and deposited on HOPG. (Adapted from Ref. [32], 2006, with permission from American Chemical Society.)...
Figure 9. XRD patters for HMM-1, RhPt/HMM-1 (non-treated), and RhPt/HMM-1 (scC02-treated). (a) Low 20 angle region and (b) high 26 angle region. Figure 9. XRD patters for HMM-1, RhPt/HMM-1 (non-treated), and RhPt/HMM-1 (scC02-treated). (a) Low 20 angle region and (b) high 26 angle region.
Tauber Hmm. Interesting. They each have the same disease . [Pg.262]

De Koning GJM,Van Bilesen HMM, Lemstra PJ, HazenbergW,Withold B, Preusting H,Van der Galien JG, Schirmer A, Jendrossek D (1994) Polymer 35 2090... [Pg.236]


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See also in sourсe #XX -- [ Pg.548 ]

See also in sourсe #XX -- [ Pg.548 ]




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Are HMMs a good model of speech

Classification with HMMs

Fault Diagnosis Using HMMs

Fault Diagnosis Using Triangular Episodes and HMMs

Fault Diagnosis Using Wavelet-Domain HMMs

HMM approach

HMM synthesis systems

Heat Management Module (HMM)

Labelling databases with HMMs

Profile (HMM) Patterns

Recognising with HMMs

Signal Processing in HMM synthesis

The HMM formalism

Training HMMS

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