20 papers · ranked by Valyu relevance
Alejandro Moreo, Andrea Esuli, Fabrizio Sebastiani
QuaPy is an open-source framework for performing quantification (a.k.a. supervised prevalence estimation), written in Python. Quantification is the task of training quantifiers via supervised learning, where a quantifier is a predictor that estimates the relative frequencies (a.k.a. prevalence values) of the classes of…
Ruben Shrestha, Andres V. Reyes, Peter R. Baker, Zhi-Yong Wang + 2 more
Metabolic labeling using stable isotopes is widely used for the relative quantification of proteins in proteomic studies. In plants, metabolic labeling using ^15^N has great potential, but the associated complexity of data analysis has limited its usage. Here, we present the ^15^N stable-isotope labeled protein…
Ruben Shrestha, Andres V. Reyes, Peter R. Baker, Zhi-Yong Wang + 2 more
'Robert J. Chalkley' 'Shou-Ling Xu'] Metabolic labeling using stable isotopes is widely used for the relative quantification of proteins in proteomic studies. In plants, metabolic labeling using 15N has great potential, but the associated complexity of data analysis has limited its usage. Here, we present the 15N…
Alejandro Moreo, Fabrizio Sebastiani, Sergio Consoli
Sentiment quantification is the task of training, by means of supervised learning, estimators of the relative frequency (also called “prevalence”) of sentiment-related classes (such as Positive, Neutral, Negative) in a sample of unlabelled texts. This task is especially important when these texts are tweets, since the…
Eszter Csibra, Guy-Bart Stan
This paper presents a generalisable method for the calibration of fluorescence readings on microplate readers, in order to convert arbitrary fluorescence units into absolute units. FPCountR relies on the generation of bespoke fluorescent protein (FP) calibrants, assays to determine protein concentration and activity…
Monica Di Fiore, Marta Kuc-Czarnecka, Samuele Lo Piano, Arnald Puy + 1 more
'Andrea Saltelli'] The present work looks at what we call “the multiverse of quantification”, where visible and invisible numbers permeate all aspects and venues of life. We review the contributions of different authors who focus on the roles of quantification in society, with the aim of capturing different and…
Andrea Bender
Numeration systems are cognitive tools that can be used to assess both discrete and continuous magnitudes (by counting and measuring, respectively). The presence and numerical value of a base in such systems have implications on several levels: They shape the system structure in creating higher (counting) units; they…
Xiangrong Tang, Yunqing Wen, Rong Qin, Jishen Zhang + 4 more
Quantitative polymerase chain reaction (qPCR) is limited in measuring absolute nucleic acid copy numbers due to the inherent variability of calibrators. Here, we introduce the Quantal PCR (quPCR), a novel method that eliminates the need for calibrators by defining an intrinsic quantal unit derived from the…
Sharon S. Newman, Linus A. Hein, Alexandra M. Adams, H. Tom Soh
Gold standard immunoassays depend on specific affinity reagents for accurate molecular quantification. Any cross-reactivity of affinity reagents, wherein the reagent non-specifically binds to unintended molecules, can create false positive binding signals and result in inaccurate quantification of analytes. Mitigating…
Kyu-Seek Kim, Jun-Su Bae, Hyuk-Jin Moon, Do-Young Kim + 2 more
'Cam Donly'] Simple Summary In the medical and pharmaceutical industries, insect cell lines are used to produce useful recombinant proteins, with their production necessitating the genetic engineering of recombinant insect viruses. Recombinant viruses can be used in experiments according to a virus quantification…
Sascha M. Kuhn, Elisa Nerli, Jifeng Liu, Sylvia Kaufmann + 6 more
Genetically encoded fluorescent biosensors are widely used to monitor small molecule and ion levels in living cells. Quantitative FRET and FLIM sensors and highly sensitive intensiometric sensors have been developed for many analytes. Notwithstanding notable advances over the last years, a universal high-performance…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
Zhe Du, Sebastian F. Behrens, Zhe-Xue Quan
Quantitative real-time PCR of phylogenetic and functional marker genes is among the most commonly used techniques to quantify the abundance of microbial taxa in environmental samples. However, in most environmental applications, the approach is a rough assessment of population abundance rather than an exact absolute…
Elizaveta I. Shestoperova, Daniil G. Ivanov, Eric R. Strieter
The diversity of ubiquitin modifications calls for methods to better characterize ubiquitin chain linkage, length, and morphology. Here, we use multiple linear regression analysis coupled with ion mobility mass spectrometry (IM-MS) to quantify the relative abundance of different ubiquitin dimer isomers. We demonstrate…
Savely G. Karshenboim
The quantitative understanding of Nature in physics takes the form of the physical laws, that set relations between different properties. We use the name 'quantity' for any quantitative property, which enters the quantitative laws. For instance, we would consider the electric field E~ as a quantity rather than its…
Maria H. Rasmussen, Chenru Duan, Heather J. Kulik, Jan Halborg Jensen
With the increasingly more important role of machine learning (ML) models in chemical research, the need for putting a level of confidence to the model predictions naturally arises. Several methods for obtaining uncertainty estimates have been proposed in recent years but consensus on the evaluation of these have yet…
Yurii V. Brezhnev
Clarifying the nature of the quantum state |Ψi is at the root of the problems with insight into (counterintuitive) quantum postulates. We provide a direct—and mathaxiom free—empirical derivation of this object as an element of a vector space. Establishing the linearity of this structure—quantum superposition—is based…
Domagoj Dorešić, Stephan Grein, Jan Hasenauer
Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. The parameters of these models are commonly estimated from experimental data. Yet, experimental data generated from different techniques do not provide direct information about the state of the…
Jonito Aerts Arguëlles
of Visual Perception Authors: ['Jonito Aerts Arguëlles'] We study the phenomenon of categorical perception within the quantum measurement process. The mechanism underlying this phenomenon consists in dilating stimuli being perceived to belong to different categories and contracting stimuli being perceived to belong to…
David Thompson, Johan Gielis
Our understanding of quantum phenomena often begins with simple particle-in-a-box style problems, the solutions of which introduce the student to foundational quantum concepts such as degeneracy and quantization. Simple model geometries of confinement afford analytic solutions, which are readily derivable, easily…