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Materials managers do not really control most hospital inventory. As indicated in the first article in this series published in the previous issue, there is more official inventory in user areas under user control than exists in general stores, central supply, and/or SPD. In addition, users control all unofficial inventory which HMM did not even attempt to measure.
The epithelium of normal subjects (NE) and that in cases of psoriasis vulgaris, or PV, (PVE) were studied using DACM-HMM staining. In the living cell layer of NE, strong fluorescence was observed in the cell margins, and these bands of fluorescence were narrower in the granular layer than in the basal and squamous layers. In PV, the bands were broad in the lower and middle strata of the squamous layer, and attenuated in the upper strata. Accompanying keratinization, the distribution of F-actin in the keratinocytes was thought to vary. The variations in fluorescence in the lower and middle squamous layer strata of PVE may be attributed to increase of F-actin in the cell margins.
A hidden Markov model for gene finding consists of submodels for coding regions, splice sites, introns, intergenic regions and possibly more. It is described how to estimate the model as a whole from labeled sequences instead of estimating the individual parts independently from subsequences. It is argued that the standard maximum likelihood estimation criterion is not optimal for training such a model. Instead of maximizing the probability of the DNA sequence, one should maximize the probability of the correct prediction. Such a criterion, called conditional maximum likelihood, is used for the gene finder 'HMM-gene'. A new (approximative) algorithm is described, which finds the most probable prediction summed over all paths yielding the same prediction. We show that these methods contribute significantly to the high performance of HMMgene.
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Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.
Truncated mutants of smooth muscle myosin containing various lengths of the S2 portion were expressed in Sf9 cells and purified. Truncated myosin having a heavy chain molecular mass of 128 kDa and larger formed a stable dimer, while 108 kDa myosin remained a monomer. On the other hand, 114 and 110 kDa myosins existed as both monomer and dimer. The enzymatic activity and also the in vitro actin sliding activity of these mutant myosins were measured, and the following findings were obtained. (1) Both the actin sliding activity and the actin-activated ATPase activity showed phosphorylation dependence when myosin forms a dimer while the monomeric form was phosphorylation-independent. This indicates that the interaction between the two heads is operating and critical for the regulation. (2) The actin sliding velocity of the dimer form was twice as large as that of the monomer form, while the actin-activated ATPase activity of the two forms was identical, suggesting that the mechano-chemical efficiency is affected by the interaction between the two heads. (3) The depression of the Mg(2+)-ATPase activity of myosin at low ionic strength, characteristic of the 6S-10S transition of smooth muscle myosin, is abolished with the monomer form, suggesting that the association of the two heads is critical for the 6S-10S transition.
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Protein family databases are an important resource for protein annotation and understanding protein evolution and function. In recent years hidden Markov models (HMMs) have become one of the key technologies used for detection of members of these families. This paper reviews the Pfam, TIGRFAMs and SMART databases that use the profile-HMMs provided by the HMMER package.
Sarment is a package of Python modules for easy building and manipulation of sequence segmentations. It provides efficient implementation of usual algorithms for hidden Markov Model computation, as well as for maximal predictive partitioning. Owing to its very large variety of criteria for computing segmentations, Sarment can handle many kinds of models. Because of object-oriented programming, the results of the segmentation are very easy tomanipulate.
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The aim is to model "activity" performed by a group of moving and interacting objects (which can be people, cars, or different rigid components of the human body) and use the models for abnormal activity detection. Previous approaches to modeling group activity include co-occurrence statistics (individual and joint histograms) and dynamic Bayesian networks, neither of which is applicable when the number of interacting objects is large. We treat the objects as point objects (referred to as "landmarks") and propose to model their changing configuration as a moving and deforming "shape" (using Kendall's shape theory for discrete landmarks). A continuous-state hidden Markov model is defined for landmark shape dynamics in an activity. The configuration of landmarks at a given time forms the observation vector, and the corresponding shape and the scaled Euclidean motion parameters form the hidden-state vector. An abnormal activity is then defined as a change in the shape activity model, which could be slow or drastic and whose parameters are unknown. Results are shown on a real abnormal activity-detection problem involving multiple moving objects.
The contractile tentacles of the suctorian Discophrya collini contain a central microtubular axoneme as well as filamentous structures in the cortical epiplasm and in a fibrous collar around the axoneme at the tentacle base. The nature and possible roles of these components has been investigated by the use of reactivatable glycerinated cells. In these a mean tentacle contraction to 70% of the original length could be achieved by a 5-min treatment with a reaction mixture containing ATP, calcium and magnesium ions, the same treatment giving retraction to 30% in living cells. Both the microtubules of the axoneme and the filaments of the fibrous collar and epiplasm were present in the glycerinated cells, suggesting that these components consist of large water-insoluble molecules. The addition of heavy meromyosin to whole glycerinated cells resulted in the appearance of 36-50-nm spaced "tails" or filaments attached to the epiplasmic fibres and the aggregation of 3-6-nm filaments and electron-dense material in the region of the fibrous collar. Neither of these 2 features was apparent after treatment with ATP. It is suggested that actin-like filaments are localized in the region of the fibrous collar and in the epiplasm, and that these are involved in tentacle retraction; whilst the microtubules of the axoneme are concerned with feeding, and play only a cytoskeletal role in the contractile mechanism.
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