Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Fine-grained simulations of the microenvironment of vascularized tumours.

ABSTRACT: One of many important features of the tumour microenvironment is that it is a place of active Darwinian selection where different tumour clones become adapted to the variety of ecological niches that make up the microenvironment. These evolutionary processes turn the microenvironment into a powerful source of tumour heterogeneity and contribute to the development of drug resistance in cancer. Here, we describe a computational tool to study the ecology of the microenvironment and report results about the ecology of the tumour microenvironment and its evolutionary dynamics.

SUBMITTER: Fredrich T

PROVIDER: S-EPMC6690935 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Fine-grained simulations of the microenvironment of vascularized tumours.

Fredrich Thierry T Rieger Heiko H Chignola Roberto R Milotti Edoardo E

Scientific reports 20190812 1

One of many important features of the tumour microenvironment is that it is a place of active Darwinian selection where different tumour clones become adapted to the variety of ecological niches that make up the microenvironment. These evolutionary processes turn the microenvironment into a powerful source of tumour heterogeneity and contribute to the development of drug resistance in cancer. Here, we describe a computational tool to study the ecology of the microenvironment and report results a ...[more]

PMID: 31406276

Similar Datasets

Coupling Coarse-Grained to Fine-Grained Models via Hamiltonian Replica Exchange.

Project description:The energy landscape of biomolecular systems contains many local minima that are separated by high energy barriers. Sampling this landscape in molecular dynamics simulations is a challenging task and often requires the use of enhanced sampling techniques. Here, we increase the sampling efficiency by coupling the fine-grained (FG) GROMOS force field to the coarse-grained (CG) Martini force field via the Hamiltonian replica exchange method (HREM). We tested the efficiency of this procedure using a lutein/octane system. In traditional simulations, cis-trans transitions of lutein are barely observed due to the high energy barrier separating these states. However, many of these transitions are sampled with our HREM scheme. The proposed method offers new possibilities for enhanced sampling of biomolecular conformations, making use of CG models without compromising the accuracy of the FG model.

| S-EPMC7426904 | biostudies-literature

Fine-grained statistical structure of speech.

Project description:In spite of its acoustic diversity, the speech signal presents statistical regularities that can be exploited by biological or artificial systems for efficient coding. Independent Component Analysis (ICA) revealed that on small time scales (∼ 10 ms), the overall structure of speech is well captured by a time-frequency representation whose frequency selectivity follows the same power law in the high frequency range 1-8 kHz as cochlear frequency selectivity in mammals. Variations in the power-law exponent, i.e. different time-frequency trade-offs, have been shown to provide additional adaptation to phonetic categories. Here, we adopt a parametric approach to investigate the variations of the exponent at a finer level of speech. The estimation procedure is based on a measure that reflects the sparsity of decompositions in a set of Gabor dictionaries whose atoms are Gaussian-modulated sinusoids. We examine the variations of the exponent associated with the best decomposition, first at the level of phonemes, then at an intra-phonemic level. We show that this analysis offers a rich interpretation of the fine-grained statistical structure of speech, and that the exponent values can be related to key acoustic properties. Two main results are: i) for plosives, the exponent is lowered by the release bursts, concealing higher values during the opening phases; ii) for vowels, the exponent is bound to formant bandwidths and decreases with the degree of acoustic radiation at the lips. This work further suggests that an efficient coding strategy is to reduce frequency selectivity with sound intensity level, congruent with the nonlinear behavior of cochlear filtering.

| S-EPMC7083313 | biostudies-literature

Coarse-grained dynamic RNA titration simulations.

Project description:Electrostatic interactions play a pivotal role in many biomolecular processes. The molecular organization and function in biological systems are largely determined by these interactions. Owing to the highly negative charge of RNA, the effect is expected to be more pronounced in this system. Moreover, RNA base pairing is dependent on the charge of the base, giving rise to alternative secondary and tertiary structures. The equilibrium between uncharged and charged bases is regulated by the solution pH, which is therefore a key environmental condition influencing the molecule's structure and behaviour. By means of constant-pH Monte Carlo simulations based on a fast proton titration scheme, coupled with the coarse-grained model HiRE-RNA, molecular dynamic simulations of RNA molecules at constant pH enable us to explore the RNA conformational plasticity at different pH values as well as to compute electrostatic properties as local pK a values for each nucleotide.

| S-EPMC6501344 | biostudies-literature

Self reward design with fine-grained interpretability.

Project description:The black-box nature of deep neural networks (DNN) has brought to attention the issues of transparency and fairness. Deep Reinforcement Learning (Deep RL or DRL), which uses DNN to learn its policy, value functions etc, is thus also subject to similar concerns. This paper proposes a way to circumvent the issues through the bottom-up design of neural networks with detailed interpretability, where each neuron or layer has its own meaning and utility that corresponds to humanly understandable concept. The framework introduced in this paper is called the Self Reward Design (SRD), inspired by the Inverse Reward Design, and this interpretable design can (1) solve the problem by pure design (although imperfectly) and (2) be optimized like a standard DNN. With deliberate human designs, we show that some RL problems such as lavaland and MuJoCo can be solved using a model constructed with standard NN components with few parameters. Furthermore, with our fish sale auction example, we demonstrate how SRD is used to address situations that will not make sense if black-box models are used, where humanly-understandable semantic-based decision is required.

| S-EPMC9886969 | biostudies-literature

Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels.

Project description:Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. We release a deep learning model for rapid object detection and precise information on the identification, locality, and counts of cored plaques and cerebral amyloid angiopathies (CAAs). We trained this object detector using a repurposed image-tile dataset without any human-drawn bounding boxes. We evaluated the detector on a new manually-annotated dataset of whole slide images (WSIs) from three institutions, four staining procedures, and four human experts. The detector matched the cohort of neuropathology experts, achieving 0.64 (model) vs. 0.64 (cohort) average precision (AP) for cored plaques and 0.75 vs. 0.51 AP for CAAs at a 0.5 IOU threshold. It provided count and locality predictions that correlated with gold-standard CERAD-like WSI scoring (p=0.07± 0.10). The openly-available model can quickly score WSIs in minutes without a GPU on a standard workstation.

| S-EPMC9882138 | biostudies-literature

FiCoS: A fine-grained and coarse-grained GPU-powered deterministic simulator for biochemical networks.

Project description:Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can be tested by means of targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the one hand, detailed mechanistic models can involve hundreds or thousands of molecular species and their intermediate complexes, as well as hundreds or thousands of chemical reactions, a situation generally occurring in rule-based modeling. On the other hand, the computational analysis of a model typically requires the execution of a large number of simulations for its calibration, or to test the effect of perturbations. As a consequence, the computational capabilities of modern Central Processing Units can be easily overtaken, possibly making the modeling of biochemical networks a worthless or ineffective effort. To the aim of overcoming the limitations of the current state-of-the-art simulation approaches, we present in this paper FiCoS, a novel "black-box" deterministic simulator that effectively realizes both a fine-grained and a coarse-grained parallelization on Graphics Processing Units. In particular, FiCoS exploits two different integration methods, namely, the Dormand-Prince and the Radau IIA, to efficiently solve both non-stiff and stiff systems of coupled Ordinary Differential Equations. We tested the performance of FiCoS against different deterministic simulators, by considering models of increasing size and by running analyses with increasing computational demands. FiCoS was able to dramatically speedup the computations up to 855×, showing to be a promising solution for the simulation and analysis of large-scale models of complex biological processes.

| S-EPMC8476010 | biostudies-literature

Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels.

Project description:Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. We release a deep learning model for rapid object detection and precise information on the identification, locality, and counts of cored plaques and cerebral amyloid angiopathy (CAA). We trained this object detector using a repurposed image-tile dataset without any human-drawn bounding boxes. We evaluated the detector on a new manually-annotated dataset of whole slide images (WSIs) from three institutions, four staining procedures, and four human experts. The detector matched the cohort of neuropathology experts, achieving 0.64 (model) vs. 0.64 (cohort) average precision (AP) for cored plaques and 0.75 vs. 0.51 AP for CAAs at a 0.5 IOU threshold. It provided count and locality predictions that approximately correlated with gold-standard human CERAD-like WSI scoring (p = 0.07 ± 0.10). The openly-available model can quickly score WSIs in minutes without a GPU on a standard workstation.

| S-EPMC10290693 | biostudies-literature

Fine-grained dengue forecasting using telephone triage services.

Project description:Thousands of lives are lost every year in developing countries for failing to detect epidemics early because of the lack of real-time disease surveillance data. We present results from a large-scale deployment of a telephone triage service as a basis for dengue forecasting in Pakistan. Our system uses statistical analysis of dengue-related phone calls to accurately forecast suspected dengue cases 2 to 3 weeks ahead of time at a subcity level (correlation of up to 0.93). Our system has been operational at scale in Pakistan for the past 3 years and has received more than 300,000 phone calls. The predictions from our system are widely disseminated to public health officials and form a critical part of active government strategies for dengue containment. Our work is the first to demonstrate, with significant empirical evidence, that an accurate, location-specific disease forecasting system can be built using analysis of call volume data from a public health hotline.

| S-EPMC4942339 | biostudies-literature

Software evolution: the lifetime of fine-grained elements.

Project description:A model regarding the lifetime of individual source code lines or tokens can estimate maintenance effort, guide preventive maintenance, and, more broadly, identify factors that can improve the efficiency of software development. We present methods and tools that allow tracking of each line's or token's birth and death. Through them, we analyze 3.3 billion source code element lifetime events in 89 revision control repositories. Statistical analysis shows that code lines are durable, with a median lifespan of about 2.4 years, and that young lines are more likely to be modified or deleted, following a Weibull distribution with the associated hazard rate decreasing over time. This behavior appears to be independent from specific characteristics of lines or tokens, as we could not determine factors that influence significantly their longevity across projects. The programing language, and developer tenure and experience were not found to be significantly correlated with line or token longevity, while project size and project age showed only a slight correlation.

| S-EPMC7959608 | biostudies-literature

Fine-grained time course of verb aspect processing.

Project description:Sentence processing is known to be highly incremental. Speakers make incremental commitments as the sentence unfolds, dynamically updating their representations based on the smallest pieces of information from the incoming speech stream. Less is known about linguistic processing on the sub-word level, especially with regard to abstract grammatical information. This study employs the Visual World Paradigm to investigate the processing of grammatical aspect by Russian-speaking adults (n = 124). Aspectual information is encoded relatively early within the Russian verb which makes this an ideal testing ground to investigate the incrementality of grammatical processing on the sub-word level. Participants showed preference for pictures of ongoing events when they heard sentences involving Imperfective verbs, and for pictures of completed events when they heard sentences involving Perfective verbs. Crucially, the analysis of the participants' eye-movements showed that they exhibited preference for the target picture already before they heard the end of the verb. Moreover, the latency of this effect depended on where the aspectual information was encoded within the verb. These results indicate that the processing and integration of grammatical aspect information can happen rapidly and incrementally on a fine-grained word-internal level. Methodologically, the study draws together a set of analytical techniques which can be fruitfully applied to the analysis of effect latencies in a wide range of studies within the Visual World eye-tracking paradigm.

| S-EPMC8880397 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data