Article
Computer Science, Theory & Methods
Yunbo Tang, Dan Chen, Xiaoli Li
Summary: The study highlights the importance of dimensionality reduction in brain imaging data analysis, categorizing research based on the scale, order, and linearity of the data, while defining criteria for qualitative evaluations. By reducing dimensionality, key insights can be revealed and understanding of brain functional states can be enhanced.
ACM COMPUTING SURVEYS
(2021)
Review
Biochemical Research Methods
Jianbo Fu, Ying Zhang, Jin Liu, Xichen Lian, Jing Tang, Feng Zhu
Summary: Individual variations in drug efficacy, side effects, and adverse drug reactions present a challenge in drug research. Pharmacometabonomics aims to understand drug pharmacokinetics and monitor metabolic pathways. This review discusses technological advances, analytical techniques, data processing strategies, and databases in pharmacometabonomics for personalized medicine.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Jun Yan, Hongning Zhai, Ling Zhu, Sasha Sa, Xiaojun Ding
Summary: obaDIA is a comprehensive automated tool for analyzing quantitative proteomics data, supporting various abundance matrices and providing rich result visualization and analysis functions.
Article
Environmental Sciences
Alberto Arienzo, Bruno Aiazzi, Luciano Alparone, Andrea Garzelli
Summary: The performance of pansharpening methods may depend on their input data format, with methods based on multiresolution analysis being unaffected by the data format. Conversely, the format is crucial for component substitution methods, and quality measurements may also depend on the data format. Additionally, the performance of methods can vary depending on whether the data format is floating-point or fixed-point.
Article
Mathematics, Interdisciplinary Applications
Serkan Balli
Summary: The Covid-19 pandemic is the most important health disaster the world has faced in the past eight months, predicting its trend has become a challenge. A study analyzed COVID-19 data and proposed a time series prediction model, estimating the global pandemic will peak at the end of January 2021 with approximately 80 million people cumulatively infected.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Biochemical Research Methods
Marco Cappellato, Giacomo Baruzzo, Barbara Di Camillo
Summary: The development of high throughput DNA sequencing techniques has facilitated the study of complex microbial systems. Differential abundance analysis has led to important conclusions in various fields, but the lack of known biological truth makes validating the results challenging.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Green & Sustainable Science & Technology
A. Ayik, N. Ijumba, C. Kabiri, P. Goffin
Summary: The study conducted a preliminary assessment of wind resources in South Sudan, obtaining data on wind quality at different locations and assessing its suitability for wind power projects. The results indicate potential for small-scale wind turbine development, particularly in the north-north eastern regions of the country. Further exploration is recommended for deploying large-scale wind turbines in these areas and investigating wind resources in other locations.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Geosciences, Multidisciplinary
Liyang Xiong, Sijin Li, Guoan Tang, Josef Strobl
Summary: Terrain is a crucial natural geographic feature that plays a significant role in physical processes. The fields of geomorphometry and terrain analysis have provided abundant topographic data and tools, which have contributed to the understanding of geomorphology, hydrology, soil science, and geographic information systems (GIS). Recent advancements in analysis theory, methods, data acquisition techniques, and analysis platforms have facilitated the interpretation of topographic characteristics and associated mechanisms and processes. Future directions include addressing challenges in data collection and construction, expanding the application of efficient analysis frameworks and tools, and integrating terrain analysis with other disciplines for cross-analysis purposes.
EARTH-SCIENCE REVIEWS
(2022)
Article
Chemistry, Analytical
Carolina Rojas Ramirez, Jessica A. Espino, Lisa M. Jones, Daniel A. Polasky, Alexey I. Nesvizhskii
Summary: Monitoring protein structure before and after environmental alterations can provide insights into protein function. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry allows for monitoring of structural rearrangements by exposing proteins to radicals. However, the challenges of processing FPOP data have limited its proteome-scale uses. In this study, a computational workflow was developed to analyze FPOP data sets more efficiently, enabling the identification of modified peptide spectra at a faster rate than previous methods.
ANALYTICAL CHEMISTRY
(2023)
Article
Multidisciplinary Sciences
Emil Maag, Archana Kulasingam, Erik Lerkevang Grove, Kamilla Sofie Pedersen, Steen Dalby Kristensen, Anne-Mette Hvas
Summary: In this study, machine learning methods were employed to analyze multiplex protein data from patients with ST-elevation myocardial infarction. It was found that 26 out of 92 proteins significantly distinguished between the acute and stable phases, with five proteins playing a key role in this differentiation. The study demonstrated the potential of machine learning in identifying novel predictive biomarkers in patients with STEMI.
SCIENTIFIC REPORTS
(2021)
Article
Mathematics
Joaquim Fernando Pinto da Costa, Manuel Cabral
Summary: The importance of statistical methods in analyzing complex and large datasets to find patterns and trends has increased significantly due to the exponential growth of data. The insights obtained from data understanding enable quick decision-making and provide a competitive advantage. This paper comprehensively and systematically reviews the recent developments in data mining.
Review
Biochemical Research Methods
Chao Li, Zhenbo Gao, Benzhe Su, Guowang Xu, Xiaohui Lin
Summary: Omics technology includes genomics, epigenomics, transcriptomics, proteomics, and metabolomics, providing new ways to study disease diagnosis and prognosis. However, the large and complex nature of Omics data makes the method used to analyze the data crucial. In the past decade, advances in biomarker discovery methods based on Omics data have been categorized into individual feature analysis, combinatorial feature analysis, and network analysis, with challenges and perspectives discussed.
ANALYTICAL AND BIOANALYTICAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Mir Henglin, Brian L. Claggett, Joseph Antonelli, Mona Alotaibi, Gino Alberto Magalang, Jeramie D. Watrous, Kim A. Lagerborg, Gavin Ovsak, Gabriel Musso, Olga V. Demler, Ramachandran S. Vasan, Martin G. Larson, Mohit Jain, Susan Cheng
Summary: This study compares the performance of traditional and newer statistical learning methods in different types of metabolomics data and finds that, in the analysis of human metabolomics data, multivariate methods perform better than univariate methods as the number of study subjects increases.
Article
Multidisciplinary Sciences
Vadim Demichev, Lukasz Szyrwiel, Fengchao Yu, Guo Ci Teo, George Rosenberger, Agathe Niewienda, Daniela Ludwig, Jens Decker, Stephanie Kaspar-Schoenefeld, Kathryn S. Lilley, Michael Muelleder, Alexey Nesvizhskii, Markus Ralser
Summary: The dia-PASEF technology utilizes ion mobility separation to reduce signal interference and enhance sensitivity in proteomic experiments. This study introduces a novel algorithm and software solution that significantly improves proteomic depth in dia-PASEF experiments, particularly for fast experiments and those with limited sample sizes.
NATURE COMMUNICATIONS
(2022)
Article
Biochemistry & Molecular Biology
Anders Hagen Jarmund, Torfinn Stove Madssen, Guro F. Giskeodegard
Summary: This paper introduces the statistical method ASCA(+) framework for analyzing multivariate data in biomedical research, as well as the application of the ALASCA package in R language. The package is suitable for longitudinal data and has the convenience of adjusting covariates.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2022)
Article
Physics, Particles & Fields
Peter Athron, Csaba Balazs, Andrew Fowlie, Yang Zhang
EUROPEAN PHYSICAL JOURNAL C
(2020)
Article
Astronomy & Astrophysics
Andrew Fowlie, Will Handley, Liangliang Su
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2020)
Article
Statistics & Probability
Andrew Fowlie
Summary: In an attempt to address the Jeffreys-Lindley paradox, we explore finding priors that are completely indifferent to sample size. We show that while an improper scale-invariant prior is obtained, a truncated scale-invariant prior can delay the dependence on sample size. Additionally, we shed light on the paradox by relating it to the improper nature of the scale-invariant prior.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2022)
Article
Astronomy & Astrophysics
Andrew Fowlie, Will Handley, Liangliang Su
Summary: The article introduces a modified version of nested sampling (NS) algorithm that can handle plateaus in the likelihood function and can be retrospectively applied to runs from popular NS software. The algorithm evicts live points in plateaus one by one without replacement, addressing the faulty estimates produced by traditional NS algorithm when dealing with plateaus. The simplicity of the modification suggests that it should become the canonical version of Skilling's NS algorithm.
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
(2021)
Article
Physics, Particles & Fields
Csaba Balazs, Melissa van Beekveld, Sascha Caron, Barry M. Dillon, Ben Farmer, Andrew Fowlie, Eduardo C. Garrido-Merchan, Will Handley, Luc Hendriks, Gudlaugur Johannesson, Adam Leinweber, Judita Mamuzic, Gregory D. Martinez, Sydney Otten, Roberto Ruiz de Austri, Pat Scott, Zachary Searle, Bob Stienen, Joaquin Vanschoren, Martin White
Summary: The research focused on optimization problems prevalent in particle and astrophysics, evaluating various global optimization algorithms and drawing general conclusions on their relative merits for different functions.
JOURNAL OF HIGH ENERGY PHYSICS
(2021)
Article
Statistics & Probability
Andrew Fowlie
Summary: The Neyman-Pearson lemma applies to Bayes factors when considering expected type-1 and type-2 error rates, with Bayes factor as the test statistic maximizing expected power for fixed expected type-1 error rate. For Bayes factors involving a simple null hypothesis, the expected type-1 error rate is equivalent to the frequentist type-1 error rate. The connection between the Karlin-Rubin theorem, uniformly most powerful tests, and Bayes factors can provide frequentist motivations for computing Bayes factors and potentially help reconcile differences between Bayesians and frequentists.
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
(2021)
Article
Physics, Particles & Fields
Peter Athron, Neal Avis Kozar, Csaba Balazs, Ankit Beniwal, Sanjay Bloor, Torsten Bringmann, Joachim Brod, Christopher Chang, Jonathan M. Cornell, Ben Farmer, Andrew Fowlie, Tomas E. Gonzalo, Will Handley, Felix Kahlhoefer, Anders Kvellestad, Farvah Mahmoudi, Markus T. Prim, Are Raklev, Janina J. Renk, Andre Scaffidi, Pat Scott, Patrick Stoecker, Aaron C. Vincent, Martin White, Sebastian Wild, Jure Zupan
Summary: In this study, a wide class of WIMP dark matter models were assessed in light of the latest experimental results using the global fitting framework GAMBIT. The global analysis of effective field theory operators revealed challenges in satisfying all constraints simultaneously while maintaining EFT validity at LHC energies. However, large regions of viable parameter space were found where the EFT is valid and the relic density can be reproduced, suggesting that WIMPs can still account for the DM of the universe while being consistent with the latest data.
EUROPEAN PHYSICAL JOURNAL C
(2021)
Article
Physics, Multidisciplinary
Andrew Fowlie, Sebastian Hoof, Will Handley
Summary: This paper proposes a novel method for computing p-values based on nested sampling applied to the sampling space of the problem. Through experiments, it is shown that this method has lower computational cost and requires fewer simulations compared to traditional Monte Carlo estimates, particularly for significances greater than about 4 sigma in high-energy physics.
PHYSICAL REVIEW LETTERS
(2022)
Article
Physics, Multidisciplinary
Kyle Cranmer, Sabine Kraml, Harrison B. Prosper, Philip Bechtle, Florian U. Bernlochner, Itay M. Bloch, Enzo Canonero, Marcin Chrzaszcz, Andrea Coccaro, Jan Conrad, Glen Cowan, Matthew Feickert, Nahuel F. Ferreiro, Andrew Fowlie, Lukas Heinrich, Alexander Held, Thomas Kuhr, Anders Kvellestad, Maeve Madigan, Farvah Mahmoudi, Knut D. Mora, Mark S. Neubauer, Maurizio Pierini, Juan Rojo, Sezen Sekmen, Luca Silvestrini, Veronica Sanz, Giordon Stark, Riccardo Torre, Robert Thorne, Wolfgang Waltenberger, Nicholas Wardle, Jonas Wittbrodt
Summary: The researchers present a scientific case for systematically publishing the full statistical models to enhance the impact of experimental results. They discuss the technical developments that make this practical and provide examples to illustrate the effectiveness of detailed statistical modeling in various physics cases.
Editorial Material
Astronomy & Astrophysics
Andrew Fowlie
Summary: This paper combines multiple experimental results to provide evidence for a new fundamental particle. However, the researchers cast doubt on the strength of the evidence and obtained lower significances through reanalysis.
Review
Physics, Multidisciplinary
Shehu S. AbdusSalam, Fruzsina J. Agocs, Benjamin C. Allanach, Peter Athron, Csaba Balazs, Emanuele Bagnaschi, Philip Bechtle, Oliver Buchmueller, Ankit Beniwal, Jihyun Bhom, Sanjay Bloor, Torsten Bringmann, Andy Buckley, Anja Butter, Jose Eliel Camargo-Molina, Marcin Chrzaszcz, Jan Conrad, Jonathan M. Cornell, Matthias Danninger, Jorge de Blas, Albert De Roeck, Klaus Desch, Matthew Dolan, Herbert Dreiner, Otto Eberhardt, John Ellis, Ben Farmer, Marco Fedele, Henning Flaecher, Andrew Fowlie, Tomas E. Gonzalo, Philip Grace, Matthias Hamer, Will Handley, Julia Harz, Sven Heinemeyer, Sebastian Hoof, Selim Hotinli, Paul Jackson, Felix Kahlhoefer, Kamila Kowalska, Michael Kraemer, Anders Kvellestad, Miriam Lucio Martinez, Farvah Mahmoudi, Diego Martinez Santos, Gregory D. Martinez, Satoshi Mishima, Keith Olive, Ayan Paul, Markus Tobias Prim, Werner Porod, Are Raklev, Janina J. Renk, Christopher Rogan, Leszek Roszkowski, Roberto Ruiz de Austri, Kazuki Sakurai, Andre Scaffidi, Pat Scott, Enrico Maria Sessolo, Tim Stefaniak, Patrick Stoecker, Wei Su, Sebastian Trojanowski, Roberto Trotta, Yue-Lin Sming Tsai, Jeriek Van den Abeele, Mauro Valli, Aaron C. Vincent, Georg Weiglein, Martin White, Peter Wienemann, Lei Wu, Yang Zhang
Summary: This article discusses the unique challenges that physical theories dependent on many parameters or tested against data from multiple experiments pose to statistical inference. The authors provide clear guidance and recommendations for statistically sound inference methods, as well as readily-available software tools and standards. Examples provided in the article can be reproduced using publicly available code on Zenodo.
REPORTS ON PROGRESS IN PHYSICS
(2022)
Article
Multidisciplinary Sciences
Peter Athron, Andrew Fowlie, Chih-Ting Lu, Lei Wu, Yongcheng Wu, Bin Zhu
Summary: In this article, the authors demonstrate that the anomalies in the measurements of the W mass and the muon g - 2 are unlikely to have a common origin, but a model involving leptoquarks might explain both anomalies. The electroweak fits show that including the g - 2 measurement worsens the tension with the CDF measurement, and conversely, adjustments that alleviate the CDF tension worsen the g - 2 tension beyond 5 sigma. Therefore, regardless of the size of the hadronic contributions in the Standard Model, new physics explanations are inevitable if we adopt the CDF W mass measurement.
NATURE COMMUNICATIONS
(2023)
Article
Multidisciplinary Sciences
Greg Ashton, Noam Bernstein, Johannes Buchner, Xi Chen, Gabor Csanyi, Andrew Fowlie, Farhan Feroz, Matthew Griffiths, Will Handley, Michael Habeck, Edward Higson, Michael Hobson, Anthony Lasenby, David Parkinson, Livia B. Partay, Matthew Pitkin, Doris Schneider, Joshua S. Speagle, Leah South, John Veitch, Philipp Wacker, David J. Wales, David Yallup
Summary: This Primer examines Skilling's nested sampling algorithm and its application in Bayesian inference and multidimensional integration. The principles of nested sampling are summarized and recent developments using efficient nested sampling algorithms in high dimensions are surveyed. Detailed examples from cosmology, gravitational-wave astronomy, and materials science are provided. Finally, the Primer includes recommendations for best practices and a discussion of potential limitations and optimizations of nested sampling.
NATURE REVIEWS METHODS PRIMERS
(2022)
Article
Astronomy & Astrophysics
Peter Athron, Csaba Balazs, Andrew Fowlie, Huifang Lv, Wei Su, Lei Wu, Jin Min Yang, Yang Zhang
Summary: In this work, the impact of electroweak and Higgs precision measurements at future electron positron colliders on various supersymmetric models is studied. The results show that future precision measurements can further test the currently allowed parameter space of these models and potentially distinguish different dark matter annihilation mechanisms.
Article
Physics, Particles & Fields
Peter Athron, Csaba Balazs, Ankit Beniwal, J. Eliel Camargo-Molina, Andrew Fowlie, Tomas E. Gonzalo, Sebastian Hoof, Felix Kahlhoefer, David J. E. Marsh, Markus Tobias Prim, Andre Scaffidi, Pat Scott, Wei Su, Martin White, Lei Wu, Yang Zhang
Summary: The excess of electron recoil events observed in the XENON1T experiment has been proposed to potentially indicate axion-like particles (ALPs) originated from the Sun or dark matter halo, or due to trace amounts of tritium in the experiment. Combining XENON1T data with astrophysical probes supports the dark matter ALP hypothesis, despite the need for tuning unknown parameters. Bayesian analysis does not show strong preference for the ALP interpretation of the XENON1T excess over the background hypothesis, despite the tensions in the case of solar ALPs.
JOURNAL OF HIGH ENERGY PHYSICS
(2021)