scholarly journals From heterogeneous datasets to predictive models of embryonic development

2021 ◽  
Author(s):  
Sayantan Dutta ◽  
Aleena L. Patel ◽  
Shannon E. Keenan ◽  
Stanislav Y. Shvartsman
Keyword(s):  
Chromatin Immunoprecipitation ◽  
Computational Models ◽  
Fruit Fly ◽  
Computational Approach ◽  
Data Driven ◽  
Gene Repression ◽  
Future Studies ◽  
Heterogeneous Datasets ◽  
Quantitative Results ◽  
Genome Manipulation

AbstractModern studies of embryogenesis are increasingly quantitative, powered by rapid advances in imaging, sequencing, and genome manipulation technologies. Deriving mechanistic insights from the complex datasets generated by these new tools requires systematic approaches for data-driven analysis of the underlying developmental processes. Here we use data from our work on signal-dependent gene repression in the fruit fly, Drosophila melanogaster, to illustrate how computational models can compactly summarize quantitative results of live imaging, chromatin immunoprecipitation, and optogenetic perturbation experiments. The presented computational approach is ideally suited for integrating rapidly accumulating quantitative data and for guiding future studies of embryogenesis.

scholarly journals Integration of various scales for measurement of insomnia

2021 ◽  
pp. 263208432110100
Author(s):  
Satyendra Nath Chakrabartty
Keyword(s):  
Test Scores ◽  
Data Driven ◽  
Weighted Sum ◽  
Future Studies ◽  
Normal Probability ◽  
Equivalent Test ◽  
Item Scores ◽  
Using Data ◽  
Set Up ◽  
Different Levels

Background Scales for evaluating insomnia differ in number of items, response format, and result in different scores distributions and score ranges and may not facilitate meaningful comparisons. Objectives Transform ordinal item-scores of three scales of insomnia to continuous, equidistant, monotonic, normally distributed scores, avoiding limitations of summative scoring of Likert scales. Methods Equidistant item-scores by weighted sum using data-driven weights to different levels of different items, considering cell frequencies of Item-Levels matrix, followed by normalization and conversion to [1, 10]. Equivalent test-scores (as sum of transformed item- scores) for a pair of scales were found by Normal Probability curves. Empirical illustration given. Results Transformed test-scores are continuous, monotonic and followed Normal distribution with no outliers and tied scores. Such test-scores facilitate ranking, better classification and meaningful comparison of scales of different lengths and formats and finding equivalent score combinations of two scales. For a given value of transformed test-score of a scale, easy alternate method avoiding integration proposed to find equivalent scores of another scales. Equivalent scores of scales help to relate various cut-off scores of different scales and uniformity in interpretations. Integration of various scales of insomnia is achieved by finding one-to-one correspondence among the equivalent score of various scales with correlation over 0.99 Conclusion Resultant test-scores facilitated undertaking analysis in parametric set up. Considering the theoretical advantages including meaningfulness of operations, better comparison, use of such method of transforming scores of Likert items/test is recommended test and items, Future studies were suggested.

scholarly journals Out of the loop? On the radical and the routine in urban big data

Urban Studies ◽  
2021 ◽  
pp. 004209802110140
Author(s):  
Sarah Barns
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Computational Models ◽  
Data Driven ◽  
Urban Systems ◽  
Out Of The Loop ◽  
Urban Futures ◽  
Urban Behaviour ◽  
The City

This commentary interrogates what it means for routine urban behaviours to now be replicating themselves computationally. The emergence of autonomous or artificial intelligence points to the powerful role of big data in the city, as increasingly powerful computational models are now capable of replicating and reproducing existing spatial patterns and activities. I discuss these emergent urban systems of learned or trained intelligence as being at once radical and routine. Just as the material and behavioural conditions that give rise to urban big data demand attention, so do the generative design principles of data-driven models of urban behaviour, as they are increasingly put to use in the production of replicable, autonomous urban futures.

Computational approach for data-driven mining of upstream value-added structures

2020 ◽  
Author(s):  
N. Bukhanov ◽  
P. Trudkov ◽  
E. Vinogradova ◽  
I. Derevitskii ◽  
K. Balabaeva ◽  
...  
Keyword(s):  
Value Added ◽  
Computational Approach ◽  
Data Driven

scholarly journals A Data-Driven Approach to Development of a Taxonomy Framework for Triple Bottom Line Metrics

2019 ◽  
Vol 11 (9) ◽  
pp. 2717
Author(s):  
Fátima L. Vieira ◽  
Paulo A. Vieira ◽  
Denis A. Coelho
Keyword(s):  
Screening Tool ◽  
Triple Bottom Line ◽  
Computational Approach ◽  
Data Driven ◽  
Specific Context ◽  
Bottom Line ◽  
Conscious Decision ◽  
Data Driven Approach ◽  
The Subject ◽  
The One

This paper proposes a data-driven approach to develop a taxonomy in a data structure on list for triple bottom line (TBL) metrics. The approach is built from the authors reflection on the subject and review of the literature about TBL. The envisaged taxonomy framework grid to be developed through this approach will enable existing metrics to be classified, grouped, and standardized, as well as detect the need for further metrics development in uncovered domains and applications. The approach reported aims at developing a taxonomy structure that can be seen as a bi-dimensional table focusing on feature interrogations and characterizing answers, which will be the basis on which the taxonomy can then be developed. The interrogations column is designed as the stack of the TBL metrics features: What type of metric is it (qualitative, quantitative, or hybrid)? What is the level of complexity of the problems where it is used? What standards does it follow? How is the measurement made, and what are the techniques that it uses? In what kinds of problems, subjects, and domains is the metric used? How is the metric validated? What is the method used in its calculation? The column of characterizing answers results from a categorization of the range of types of answers to the feature interrogations. The approach reported in this paper is based on a screening tool that searches and analyzes information both within abstracts and full-text journal papers. The vision for this future taxonomy is that it will enable locating for any specific context, discern what TBL metrics are used in that context or similar contexts, or whether there is a lack of developed metrics. This meta knowledge will enable a conscious decision to be made between creating a new metric or using one of those that already exists. In this latter case, it would also make it possible to choose, among several metrics, the one that is most appropriate to the context at hand. In addition, this future framework will ease new future literature revisions, when these are viewed as updates of this envisaged taxonomy. This would allow creating a dynamic taxonomy for TBL metrics. This paper presents a computational approach to develop such taxonomy, and reports on the initial steps taken in that direction, by creating a taxonomy framework grid with a computational approach.

scholarly journals Investigating style evolution of Western classical music: A computational approach

2018 ◽  
Vol 23 (4) ◽  
pp. 486-507 ◽  
Author(s):  
Christof Weiß ◽  
Matthias Mauch ◽  
Simon Dixon ◽  
Meinard Müller
Keyword(s):  
Classical Music ◽  
Music History ◽  
Computational Approach ◽  
Unsupervised Clustering ◽  
Computational Experiments ◽  
Data Driven ◽  
Independent Evidence ◽  
Audio Recordings ◽  
Western Classical Music ◽  
Historical Periods

In musicology, there has been a long debate about a meaningful partitioning and description of music history regarding composition styles. Particularly, concepts of historical periods have been criticized since they cannot account for the continuous and interwoven evolution of style. To systematically study this evolution, large corpora are necessary suggesting the use of computational strategies. This article presents such strategies and experiments relying on a dataset of 2000 audio recordings, which cover more than 300 years of music history. From the recordings, we extract different tonal features. We propose a method to visualize these features over the course of history using evolution curves. With the curves, we re-trace hypotheses concerning the evolution of chord transitions, intervals, and tonal complexity. Furthermore, we perform unsupervised clustering of recordings across composition years, individual pieces, and composers. In these studies, we found independent evidence of historical periods that broadly agrees with traditional views as well as recent data-driven experiments. This shows that computational experiments can provide novel insights into the evolution of styles.

scholarly journals FusionDN: A Unified Densely Connected Network for Image Fusion

2020 ◽  
Vol 34 (07) ◽  
pp. 12484-12491 ◽  
Author(s):  
Han Xu ◽  
Jiayi Ma ◽  
Zhuliang Le ◽  
Junjun Jiang ◽  
Xiaojie Guo
Keyword(s):  
Image Fusion ◽  
State Of The Art ◽  
Data Driven ◽  
Single Model ◽  
Connected Network ◽  
Qualitative And Quantitative ◽  
Multiple Tasks ◽  
Different Types ◽  
Fused Image ◽  
Quantitative Results

In this paper, we present a new unsupervised and unified densely connected network for different types of image fusion tasks, termed as FusionDN. In our method, the densely connected network is trained to generate the fused image conditioned on source images. Meanwhile, a weight block is applied to obtain two data-driven weights as the retention degrees of features in different source images, which are the measurement of the quality and the amount of information in them. Losses of similarities based on these weights are applied for unsupervised learning. In addition, we obtain a single model applicable to multiple fusion tasks by applying elastic weight consolidation to avoid forgetting what has been learned from previous tasks when training multiple tasks sequentially, rather than train individual models for every fusion task or jointly train tasks roughly. Qualitative and quantitative results demonstrate the advantages of FusionDN compared with state-of-the-art methods in different fusion tasks.

scholarly journals Data-driven computational models reveal perceptual simulation in word processing

2019 ◽  
Author(s):  
Marco Alessandro Petilli ◽  
Fritz Günther ◽  
Alessandra Vergallito ◽  
Marco Ciapparelli ◽  
Marco Marelli
Keyword(s):  
Semantic Priming ◽  
Word Processing ◽  
Computational Models ◽  
Grounded Cognition ◽  
Data Driven ◽  
Continuous Scale ◽  
Behavioural Performance ◽  
Sensorimotor Information ◽  
Conceptual Equivalence ◽  
Prime Target

In their strongest formulation, theories of grounded cognition claim that concepts are made up of sensorimotor information. Following such equivalence, perceptual properties of objects should consistently influence processing, even in purely linguistic tasks, where perceptual information is neither solicited nor required. Previous studies have tested this prediction in semantic priming tasks, but they have not observed perceptual influences on participants’ performances. However, those findings suffer from critical shortcomings, which may have prevented potential visually grounded/perceptual effects from being detected. Here, we investigate this topic by applying an innovative method expected to increase the sensitivity in detecting such perceptual effects. Specifically, we adopt an objective, data-driven, computational approach to independently quantify vision-based and language-based similarities for prime-target pairs on a continuous scale. We test whether these measures predict behavioural performance in a semantic priming mega-study with various experimental settings. Vision-based similarity is found to facilitate performance, but a dissociation between vision-based and language-based effects was also observed. Thus, in line with theories of grounded cognition, perceptual properties can facilitate word processing even in purely linguistic tasks, but the behavioural dissociation at the same time challenges strong claims of sensorimotor and conceptual equivalence.

scholarly journals Data-driven modeling of cholinergic modulation of neural microcircuits: bridging neurons, synapses, and network states

2018 ◽  
Author(s):  
Srikanth Ramaswamy ◽  
Henry Markram
Keyword(s):  
Information Processing ◽  
Computational Models ◽  
Network Activity ◽  
Data Driven ◽  
Global Network ◽  
Cholinergic Modulation ◽  
Anatomy And Physiology ◽  
Synaptic Physiology ◽  
Network States

1AbstractNeuromodulators, such as acetylcholine (ACh), control information processing in neural microcircuits by regulating neuronal and synaptic physiology. Computational models and simulations enable predictions on the potential role of ACh in reconfiguring network states. As a prelude into investigating how the cellular and synaptic effects of ACh collectively influence emergent network dynamics, we developed a data-driven framework incorporating phenomenological models of the anatomy and physiology of cholinergic modulation of the neocortex. The first-draft models were integrated into a biologically detailed tissue model of neocortical microcircuitry to predict how ACh affects different types of neurons and synapses, and consequently alters global network states. Preliminary simulations not only corroborate the long-standing notion that ACh desynchronizes network activity, but also reveal a potentially finegrained control over a spectrum of neocortical states. We show that low levels of ACh, such as those during sleep, drive microcircuit activity into slow oscillations and network synchrony, whereas high ACh concentrations, such as those during wakefulness, govern fast oscillations and network asynchrony. In addition, network states modulated by ACh levels shape spike-time cross-correlations across distinct neuronal populations in strikingly different ways. These effects are likely due to the differential regulation of neurons and synapses caused by increasing levels of ACh that enhances cellular excitability by increasing neuronal activity and decreases the efficacy of local synaptic transmission by altering neurotransmitter release probability. We conclude by discussing future directions to refine the biological accuracy of the framework, which will extend its utility and foster the development of hypotheses to investigate the role of neuromodulation in neural information processing.

scholarly journals Ratio Between Lactobacillus Plantarum and Acetobacter Pomorum on the Surface of Drosophila Melanogaster Adult Flies Depends on Cuticle Melanisation

2021 ◽  
Author(s):  
Vladislav Mokeev ◽  
Yiwen Wang ◽  
Nicole Gehring ◽  
Bernard Moussian
Keyword(s):  
Drosophila Melanogaster ◽  
Lactobacillus Plantarum ◽  
Relative Abundance ◽  
Gene Editing ◽  
Fruit Fly ◽  
Wild Type ◽  
Specific Primers ◽  
Future Studies ◽  
Rdna Sequencing ◽  
Simple Protocol

Abstract Objectives As in most organisms, the surface of the fruit fly Drosophila melanogaster is associated with bacteria. In order to study the genetic parameters of this association, we developed a simple protocol for surface bacteria isolation and quantification. Results On wild-type flies maintained in the laboratory, we identified two persistently culturable species as Lactobacillus plantarum and Acetobacter pomorum by 16S rDNA sequencing. For quantification, we showered single flies for DNA extraction avoiding the rectum to prevent contamination from the gut. Using specific primers for quantitative PCR analyses, we determined the relative abundance of these two species in surface wash samples. Repeatedly, we found 20% more L. plantarum than A. pomorum . To tentatively study the importance of the cuticle for the interaction of the surface with these bacteria, applying Crispr/Cas9 gene editing in the initial wild-type flies, we generated flies mutant for the ebony gene needed for cuticle melanisation and determined the L. plantarum to A. pomorum ratio on these flies. We found that the relative abundance of L. plantarum increased substantially on ebony flies. We conclude that the cuticle chemistry is crucial for surface bacteria composition. This finding may inspire future studies on cuticle-microbiome interactions.

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