Article
Biochemistry & Molecular Biology
Ankita Agarwal, Kunal Singh, Shri Kant, Ranjit Prasad Bahadur
Summary: RNA-protein interactions play important roles in cellular machineries, but the molecular mechanism is still unclear. Study of binding interfaces is crucial for understanding molecular functioning and aberrations. Efficient computational algorithms are needed to identify protein-binding nucleotides in RNA with limited structural data compared to sequence data.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Computer Science, Information Systems
Darren Yates, Md Zahidul Islam
Summary: The FastForest algorithm, with its three optimizing components, achieves faster processing speed on hardware-constrained devices while maintaining high accuracy, suitable for both PC and smartphone platforms. Empirical testing shows excellent performance against other ensemble classifiers, surpassing them in various tests.
INFORMATION SCIENCES
(2021)
Article
Environmental Sciences
Emma C. Hall, Mark J. Lara
Summary: Uncrewed aerial systems (UASs) have been proven to be powerful tools for ecological observations, especially in measuring plant physiological and phenological traits. However, the high cost of drone-borne sensors limits their widespread use. This study evaluates the tradeoffs between off-the-shelf and sophisticated sensors for mapping plant species and functional types in a diverse grassland. The results show that off-the-shelf multispectral sensors can achieve comparable mapping accuracies by integrating phenometrics into machine learning image classifiers.
Article
Mathematics, Applied
Serpil Yalcin Kuzu
Summary: Data used in particle physics analyses often have imbalanced nature, making it difficult to identify rare events of interest from the background. This study explores the use of supervised machine learning approaches, specifically classification algorithms, to interpret skewed particle datasets. The application of a multiclass classification approach based on random forest classifier (RFC) showed promising results in the analysis of the ground state and excited states of bottomonium.
JOURNAL OF SCIENTIFIC COMPUTING
(2023)
Article
Environmental Sciences
Xiaochun Zhai, Rui Xu, Zhixiong Wang, Zhaojun Zheng, Yixuan Shou, Shengrong Tian, Lin Tian, Xiuqing Hu, Lin Chen, Na Xu
Summary: The Ku-band scatterometer called CSCAT onboard the Chinese-French Oceanography Satellite (CFOSAT) is the first spaceborne rotating fan-beam scatterometer (RFSCAT). A new algorithm using a random forest classifier is presented to classify Arctic sea ice types based on CSCAT measurement data. The algorithm extracts innovative feature parameters from orbital measurement for the first time and achieves high overall accuracy and precision for water, first-year ice (FYI), and multi-year ice (MYI). The algorithm is validated and compared with other datasets, showing good spatial homogeneity and improved detection of MYI mobility in the East Greenland region.
Article
Environmental Sciences
Luciana Nieto, Rasmus Houborg, Ariel Zajdband, Arin Jumpasut, P. V. Vara Prasad, Brad J. S. C. Olson, Ignacio A. Ciampitti
Summary: It is crucial for farmers, policymakers, and government agencies to accurately define agricultural crop phenology and its spatial-temporal variability. This study proposes using high-cadence earth observations and robust classifiers to improve the accuracy of crop phenology classification. The findings suggest that high temporal resolution data significantly enhances crop classification metrics compared to lower temporal resolution data. Additionally, the research emphasizes the criticality of high temporal resolution earth observation data for agriculture decision making.
Article
Forestry
Yihua Jin, Jingrong Zhu, Guishan Cui, Zhenhao Yin, Weihong Zhu, Dong Kun Lee
Summary: This study aims to characterize forest cover transitions and identify degraded or at-risk areas in North Korea. Using phenological information and random forest classifiers, a deforestation classification was performed. The analysis of deforestation dynamics from 1990 to 2020 revealed severe degradation and fragmentation of forests in North Korea.
Article
Cell Biology
Alireza Rouzitalab, Chadwick B. Boulay, Jeongwon Park, Julio C. Martinez-Trujillo, Adam J. Sachs
Summary: The neuronal ensembles in the lateral prefrontal cortex of non-human primates can dynamically encode and store arbitrary stimulus-response associations. These ensembles rapidly learn new associations and can retrieve multiple previously learned associations from a neuronal subspace. Additionally, knowledge of old associations facilitates the learning of new, similar associations.
Article
Gastroenterology & Hepatology
Krishnakant Saboo, Amirhossein Shamsaddini, Mihir V. Iyer, Chang Hu, Andrew Fagan, Edith A. Gavis, Melanie B. White, Michael Fuchs, Douglas M. Heuman, Masoumeh Sikaroodi, Ravishankar K. Iyer, Patrick M. Gillevet, Jasmohan S. Bajaj
Summary: This study aimed to determine the differences in fecal microbiota composition/functionality between men and women with cirrhosis and hepatic encephalopathy on differing treatments. The results showed differences in gut microbial function and composition between men and women with cirrhosis, which could be implicated in differential responses to hepatic encephalopathy therapies. Further studies linking these differences to sex-specific outcomes are needed.
JOURNAL OF HEPATOLOGY
(2021)
Article
Gastroenterology & Hepatology
Krishnakant Saboo, Nikita Petrakov, Amirhossein Shamsaddini, Andrew Fagan, Edith A. Gavis, Masoumeh Sikaroodi, Sara McGeorge, Patrick M. Gillevet, Ravishankar K. Iyer, Jasmohan S. Bajaj
Summary: Machine learning analysis shows that stool microbiota composition is more informative than saliva in differentiating between controls and patients with cirrhosis, and those with varying cirrhosis severity.
JOURNAL OF HEPATOLOGY
(2022)
Article
Environmental Sciences
Panpan Wei, Weiwei Zhu, Yifan Zhao, Peng Fang, Xiwang Zhang, Nana Yan, Hao Zhao
Summary: This study used Kenya as the study area and employed machine learning algorithms and remote sensing data to accurately and quickly map grasslands, providing important support for the stable development of the local animal husbandry economy. The research identified the optimal feature combination and classification method, laying the foundation for future land cover classification.
Article
Computer Science, Artificial Intelligence
Guiling Li, Shaolin Xu, Senzhang Wang, Philip S. Yu
Summary: Time series classification is an important task in time series data mining. This paper proposes a new TSC algorithm called FIT, which combines appropriate transformation series and interval features, and adaptsively converts the interval features of each series during formal training. Experimental results on 85 UCR time series classification datasets show that FIT achieves better accuracy while maintaining high efficiency compared to state-of-the-art methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Environmental
Yuantian Sun, Guichen Li, Junfei Zhang, Jiandong Huang
Summary: The study proposed an ensemble classifier RF-FA model for rockburst prediction, which effectively optimized the hyperparameters of RF using FA. By selecting key parameters as input variables and rockburst intensity as output, the model demonstrated high performance in independent test sets and new engineering projects, showing better accuracy compared to existing models.
BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT
(2021)
Article
Clinical Neurology
Juan Pablo Princich, Patricio Andres Donnelly-Kehoe, Alvaro Deleglise, Mariana Nahir Vallejo-Azar, Guido Orlando Pascariello, Pablo Seoane, Jose Gabriel Veron Do Santos, Santiago Collavini, Alejandro Hugo Nasimbera, Silvia Kochen
Summary: This study calculated reference volumetry values from two commonly used methods to accurately identify patients with temporal epilepsy and hippocampal sclerosis. Validation with an automatic classifier confirmed the principal role of the hippocampus and its subregions for diagnosis.
FRONTIERS IN NEUROLOGY
(2021)
Article
Chemistry, Medicinal
Robert P. Sheridan
Summary: Similar predictions are observed for the majority of molecules across different versions of the random forest models for ADMET end points. However, a small minority of molecules show substantial shifts in predictions over a few versions. These shifting molecules tend to have more accurate predictions in later versions. This Perspective investigates metrics to identify and predict substantial shifts in molecule predictions.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Medicinal
Malgorzata N. Drwal, Celien Jacquemard, Carlos Perez, Jeremy Desaphy, Esther Kellenberger
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2017)
Article
Chemistry, Multidisciplinary
Cen Gao, Jeremy Desaphy, Michal Vieth
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2017)
Article
Chemistry, Medicinal
Malgorzata N. Drwal, Guillaume Bret, Carlos Perez, Celien Jacquemard, Jeremy Desaphy, Esther Kellenberger
JOURNAL OF MEDICINAL CHEMISTRY
(2018)
Article
Chemistry, Medicinal
Noe Sturm, Jeremy Desaphy, Ronald J. Quinn, Didier Rognan, Esther Kellenberger
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2012)
Article
Chemistry, Medicinal
Jeremy Desaphy, Karima Azdimousa, Esther Kellenberger, Didier Rognan
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2012)
Article
Chemistry, Medicinal
Jeremy Desaphy, Eric Raimbaud, Pierre Ducrot, Didier Rognan
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2013)
Article
Chemistry, Medicinal
Joffrey Gabel, Jeremy Desaphy, Didier Rognan
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2014)
Article
Chemistry, Medicinal
Jeremy Desaphy, Didier Rognan
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2014)
Article
Chemistry, Multidisciplinary
G. Benay, R. Schurhammer, J. Desaphy, G. Wipff
NEW JOURNAL OF CHEMISTRY
(2011)
Article
Biochemistry & Molecular Biology
Jeremy Desaphy, Guillaume Bret, Didier Rognan, Esther Kellenberger
NUCLEIC ACIDS RESEARCH
(2015)
Article
Chemistry, Multidisciplinary
Celien Jacquemard, Malgorzata N. Drwal, Jeremy Desaphy, Esther Kellenberger
JOURNAL OF CHEMINFORMATICS
(2019)
Article
Chemistry, Medicinal
Franck Da Silva, Jeremy Desaphy, Didier Rognan