scholarly journals Cellular Reprogramming in Bursts and Phases

2021 ◽  
Author(s):  
Bradly Alicea
Keyword(s):  
Statistical Models ◽  
Temporal Structure ◽  
Cellular Reprogramming ◽  
Biochemical Process ◽  
Critical Determinant ◽  
Analytical Strategy ◽  
Gene Expression Phenotype ◽  
Cellular Population ◽  
Sources Of Variation ◽  
Insight Into

AbstractAs a biochemical process, direct cellular reprogramming is slow and complex. The early stages of this process is the most critical determinant of successful phenotypic conversion. This study provides insight into the statistical signatures that describe temporal structure in the reprogramming process. We examine two sources of variation in reprogramming cells: clonal instances from various tissues of origin and rate of expansion between these lines. Our analytical strategy involved modeling the potential of populations to reprogram, and then applying statistical models to capture this potential in action. This two-fold approach utilizes both conventional and novel techniques that allow us to infer and confirm a host of properties that define the phenomenon. These results can be summarized in a number of ways, and essentially suggest that reprogramming is organized around changes in gene expression phenotype (phases) which happens sporadically across a cellular population (bursts).

scholarly journals Modeling In-Match Sports Dynamics Using the Evolving Probability Method

2021 ◽  
Vol 11 (10) ◽  
pp. 4429
Author(s):  
Ana Šarčević ◽  
Damir Pintar ◽  
Mihaela Vranić ◽  
Ante Gojsalić
Keyword(s):  
Monte Carlo Simulation ◽  
Statistical Models ◽  
Empirical Bayes ◽  
Hybrid Approach ◽  
Real Life ◽  
Bayes Estimation ◽  
Probability Method ◽  
Specific Nature ◽  
Sport Event ◽  
Insight Into

The prediction of sport event results has always drawn attention from a vast variety of different groups of people, such as club managers, coaches, betting companies, and the general population. The specific nature of each sport has an important role in the adaption of various predictive techniques founded on different mathematical and statistical models. In this paper, a common approach of modeling sports with a strongly defined structure and a rigid scoring system that relies on an assumption of independent and identical point distributions is challenged. It is demonstrated that such models can be improved by introducing dynamics into the match models in the form of sport momentums. Formal mathematical models for implementing these momentums based on conditional probability and empirical Bayes estimation are proposed, which are ultimately combined through a unifying hybrid approach based on the Monte Carlo simulation. Finally, the method is applied to real-life volleyball data demonstrating noticeable improvements over the previous approaches when it comes to predicting match outcomes. The method can be implemented into an expert system to obtain insight into the performance of players at different stages of the match or to study field scenarios that may arise under different circumstances.

Perception of Temporal Patterns

1985 ◽  
Vol 2 (4) ◽  
pp. 411-440 ◽  
Author(s):  
Dirk-Jan Povel ◽  
Peter Essens
Keyword(s):  
Computer Program ◽  
Temporal Pattern ◽  
Basic Assumption ◽  
Temporal Structure ◽  
Internal Representation ◽  
Temporal Patterns ◽  
Internal Clock ◽  
Yield Data ◽  
Measuring Device ◽  
Insight Into

To gain insight into the internal representation of temporal patterns, we studied the perception and reproduction of tone sequences in which only the tone-onset intervals were varied. A theory of the processing of such sequences, partly implemented as a computer program, is presented. A basic assumption of the theory is that perceivers try to generate an internal clock while listening to a temporal pattern. This internal clock is of a flexible nature that adapts itself to certain characteristics of the pattern under consideration. The distribution of accented events perceived in the sequence is supposed to determine whether a clock can (and which clock will) be generated internally. Further it is assumed that if a clock is induced in the perceiver, it will be used as a measuring device to specify the temporal structure of the pattern. The nature of this specification is formalized in a tentative coding model. Three experiments are reported that test different aspects of the model. In Experiment 1, subjects reproduced various temporal patterns that only differed structurally in order to test the hypothesis that patterns more readily inducing an internal clock will give rise to more accurate percepts. In Experiment 2, clock induction is manipulated experimentally to test the clock notion more directly. Experiment 3 tests the coding portion of the model by correlating theoretical complexity of temporal patterns based on the coding model with complexity judgments. The experiments yield data that support the theoretical ideas.

scholarly journals Statistical methods for analysis of multi-harvest data from perennial pasture variety selection trials

2015 ◽  
Vol 66 (9) ◽  
pp. 947 ◽  
Author(s):  
Joanne De Faveri ◽  
Arūnas P. Verbyla ◽  
Wayne S. Pitchford ◽  
Shoba Venkatanagappa ◽  
Brian R. Cullis
Keyword(s):  
Statistical Methods ◽  
Temporal Correlation ◽  
Field Trials ◽  
Model Fit ◽  
Natural Sources ◽  
Variety Selection ◽  
Sources Of Variation ◽  
Harvest Data ◽  
Insight Into

Variety selection in perennial pasture crops involves identifying best varieties from data collected from multiple harvest times in field trials. For accurate selection, the statistical methods for analysing such data need to account for the spatial and temporal correlation typically present. This paper provides an approach for analysing multi-harvest data from variety selection trials in which there may be a large number of harvest times. Methods are presented for modelling the variety by harvest effects while accounting for the spatial and temporal correlation between observations. These methods provide an improvement in model fit compared to separate analyses for each harvest, and provide insight into variety by harvest interactions. The approach is illustrated using two traits from a lucerne variety selection trial. The proposed method provides variety predictions allowing for the natural sources of variation and correlation in multi-harvest data.

scholarly journals Queuing models of gene expression: Analytical distributions and beyond

2020 ◽  
Author(s):  
C. Shi ◽  
Y. Jiang ◽  
T. Zhou
Keyword(s):  
Gene Expression ◽  
Waiting Time ◽  
Time Distribution ◽  
Biochemical Process ◽  
Waiting Time Distribution ◽  
Molecular Memory ◽  
Queuing Model ◽  
Analytical Expression ◽  
Intermediate Reaction ◽  
Insight Into

ABSTRACTActivation of a gene is a multistep biochemical process, involving recruitments of transcription factors and histone kinases as well as modification of histones. Many of these intermediate reaction steps would have been unspecified by experiments. Therefore, classical two-state models of gene expression established based on the memoryless (or Markovian) assumption would not well describe the reality in gene expression. In fact, recent experimental data have indicated that the inactive phases of gene promoters are differently distributed, showing strong memory. Here, we use a non-exponential waiting-time distribution to model the complex activation process of a gene, and analyze a queuing model of stochastic transcription. We successfully derive the analytical expression for the mRNA distribution, which provides insight into the effect of molecular memory created by complex activating events on the mRNA expression. We find that the reduction in the waiting-time noise may result in the increase in the mRNA noise, contrary to the previous conclusion. Based on the derived distribution, we also develop a method to infer the waiting-time distribution from a known mRNA distribution. Data analysis on a realistic example verifies the validity of this method.SIGNIFICANCEActivation of a gene is a complex biochemical process and involve several intermediate reaction steps, many of which have been unspecified by experiments. Stochastic models of gene expression that were previously established based on the constant reaction rates would not well reflect the reality in gene expression. To this end, we study a queuing model of stochastic transcription which assume that the reaction waiting time follows a general distribution and derive the analytical expression for mRNA distribution. Our results provide insight into the role of molecular memory in fine-tuning the gene expression noise, and can be used to infer the underlying molecular mechanism.

scholarly journals Mode of induction of platelet-derived extracellular vesicles is a critical determinant of their phenotype and function

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
P. M. Ferreira ◽  
E. Bozbas ◽  
S. D. Tannetta ◽  
N. Alroqaiba ◽  
R. Zhou ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Size Exclusion ◽  
Biological Functions ◽  
Critical Determinant ◽  
Agonist Stimulation ◽  
Exclusion Chromatography ◽  
Average Size ◽  
And Function ◽  
Free Plasma ◽  
Insight Into

Abstract Platelet-derived extracellular vesicles (PDEVs) are the most abundant amongst all types of EVs in the circulation. However, the mechanisms leading to PDEVs release, their role in coagulation and phenotypic composition are poorly understood. PDEVs from washed platelets were generated using different stimuli and were characterised using nanoparticle tracking analysis. Procoagulant properties were evaluated by fluorescence flow cytometry and calibrated automated thrombography. EVs from plasma were isolated and concentrated using a novel protocol involving a combination of size exclusion chromatography and differential centrifugation, which produces pure and concentrated EVs. Agonist stimulation enhanced PDEV release, but did not alter the average size of EVs compared to those produced by unstimulated platelets. Agonist stimulation led to lower negatively-charged phospholipid externalization in PDEVs, which was reflected in the lower procoagulant activity compared to those generated without agonist stimulation. Circulating EVs did not have externalized negatively-charged phospholipids. None of the 4 types of EVs presented tissue factor. The mechanism by which PDEV formation is induced is a critical determinant of its phenotype and function. Importantly, we have developed methods to obtain clean, concentrated and functional EVs derived from platelet-free plasma and washed platelets, which can be used to provide novel insight into their biological functions.

scholarly journals A Cable-Borne Tram for Atmospheric Measurements along Transects

2009 ◽  
Vol 26 (3) ◽  
pp. 462-473 ◽  
Author(s):  
S. P. Oncley ◽  
K. Schwenz ◽  
S. P. Burns ◽  
J. Sun ◽  
R. K. Monson
Keyword(s):  
Temporal Structure ◽  
Three Dimensional ◽  
Carbon Dioxide Concentration ◽  
Water Drainage ◽  
Atmospheric Measurements ◽  
Arbitrary Length ◽  
Forest Canopies ◽  
Niwot Ridge ◽  
Local Water ◽  
Insight Into

Abstract A system to make atmospheric measurements from a moving trolley suspended by a stretched cable has been developed. At present, these measurements consist of wind velocity, temperature, humidity, and carbon dioxide concentration, though other sensors may be added. The track consists of cable segments attached to turns mounted on standard triangular towers. Using this approach, the path can be a closed (three dimensional) polygon of arbitrary length. This tool allows continuous, high spatial and temporal resolution sampling in environments, such as within forest canopies, not possible with other platforms. This system was used at the Niwot Ridge AmeriFlux site to obtain insight into the spatial and temporal structure of CO2, wind, and humidity fields in a natural forest ecosystem. Specifically, cool, moist, and CO2-rich air was observed to move in thin blobs downslope along the local water drainage through the subcanopy space at night.

Ecological Data Exploration

2019 ◽  
pp. 27-62
Author(s):  
Mohamed Elhadi Rahmani ◽  
Abdelmalek Amine
Keyword(s):  
Remote Sensing ◽  
Data Mining ◽  
Statistical Models ◽  
Earth Science ◽  
Data Exploration ◽  
Statistical Techniques ◽  
Ecological Data ◽  
Response Variable ◽  
Use Of Data ◽  
Sources Of Variation

Computer modeling of ecological systems is the activity of implementing computer solutions to analyze data related to the fields of remote sensing, earth science, biology, and oceans. The ecologists analyze the data to identify the relationships between a response and a set of predictors, using statistical models that do not accurately describe the main sources of variation in the response variable. Knowledge discovery techniques are often more powerful, flexible, and effective for exploratory analysis than statistical techniques. This chapter aims to test the use of data mining in ecology. It will discuss the exploration of ecological data by defining at first data mining, its advantages, and its different types. Then the authors detail the field of bio-inspiration and meta-heuristics. And finally, they give case studies from where they applied these two areas to explore ecological data.

scholarly journals Controlling mechanical properties of bio-inspired hydrogels by modulating nano-scale, inter-polymeric junctions

2014 ◽  
Vol 5 ◽  
pp. 887-894 ◽  
Author(s):  
Seonki Hong ◽  
Hyukjin Lee ◽  
Haeshin Lee
Keyword(s):  
Mechanical Properties ◽  
Biochemical Process ◽  
Peg Hydrogels ◽  
Gelation Kinetics ◽  
Nano Scale ◽  
Hard Tissues ◽  
Intermolecular Reaction ◽  
Quinone Tanning ◽  
Amine Groups ◽  
Insight Into

Quinone tanning is a well-characterized biochemical process found in invertebrates, which produce diverse materials from extremely hard tissues to soft water-resistant adhesives. Herein, we report new types of catecholamine PEG derivatives, PEG-NH-catechols that can utilize an expanded spectrum of catecholamine chemistry. The PEGs enable simultaneous participation of amine and catechol in quinone tanning crosslinking. The intermolecular reaction between PEG-NH-catechols forms a dramatic nano-scale junction resulting in enhancement of gelation kinetics and mechanical properties of PEG hydrogels compared to results obtained by using PEGs in the absence of amine groups. Therefore, the study provides new insight into designing new crosslinking chemistry for controlling nano-scale chemical reactions that can broaden unique properties of bulk hydrogels.

Stochastic Nature of Precisely Timed Spike Patterns in Visual System Neuronal Responses

1999 ◽  
Vol 81 (6) ◽  
pp. 3021-3033 ◽  
Author(s):  
M. W. Oram ◽  
M. C. Wiener ◽  
R. Lestienne ◽  
B. J. Richmond
Keyword(s):  
Visual System ◽  
Statistical Models ◽  
Temporal Structure ◽  
Response Strength ◽  
Spike Count ◽  
Neural Responses ◽  
Neuronal Responses ◽  
V1 Neurons ◽  
Stochastic Nature ◽  
Spike Patterns

Stochastic nature of precisely timed spike patterns in visual system neuronal responses. It is not clear how information related to cognitive or psychological processes is carried by or represented in the responses of single neurons. One provocative proposal is that precisely timed spike patterns play a role in carrying such information. This would require that these spike patterns have the potential for carrying information that would not be available from other measures such as spike count or latency. We examined exactly timed (1-ms precision) triplets and quadruplets of spikes in the stimulus-elicited responses of lateral geniculate nucleus (LGN) and primary visual cortex (V1) neurons of the awake fixating rhesus monkey. Large numbers of these precisely timed spike patterns were found. Information theoretical analysis showed that the precisely timed spike patterns carried only information already available from spike count, suggesting that the number of precisely timed spike patterns was related to firing rate. We therefore examined statistical models relating precisely timed spike patterns to response strength. Previous statistical models use observed properties of neuronal responses such as the peristimulus time histogram, interspike interval, and/or spike count distributions to constrain the parameters of the model. We examined a new stochastic model, which unlike previous models included all three of these constraints and unlike previous models predicted the numbers and types of observed precisely timed spike patterns. This shows that the precise temporal structures of stimulus-elicited responses in LGN and V1 can occur by chance. We show that any deviation of the spike count distribution, no matter how small, from a Poisson distribution necessarily changes the number of precisely timed spike patterns expected in neural responses. Overall the results indicate that the fine temporal structure of responses can only be interpreted once all the coarse temporal statistics of neural responses have been taken into account.

Sign in / Sign up

Export Citation Format

Share Document