Article
Biochemical Research Methods
Thien Le, Aaron Sy, Erin K. Molloy, Qiuyi Zhang, Satish Rao, Tandy Warnow
Summary: Incremental tree building (INC) is a fast converging phylogeny estimation method, but has poor accuracy for gene tree estimation; Constrained-INC approaches the accuracy of the best methods for species tree estimation and is faster.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Multidisciplinary Sciences
Ying Chen, Fan Nie, Shang-Qian Xie, Ying-Feng Zheng, Qi Dai, Thomas Bray, Yao-Xin Wang, Jian-Feng Xing, Zhi-Jian Huang, De-Peng Wang, Li-Juan He, Feng Luo, Jian-Xin Wang, Yi-Zhi Liu, Chuan-Le Xiao
Summary: The error correction and de novo assembly tool NECAT developed by the authors efficiently produces high-quality assemblies of nanopore reads. The tool utilizes adaptive read selection and a two-step progressive method to overcome the high error rates in nanopore reads.
NATURE COMMUNICATIONS
(2021)
Article
Biology
Egor Revkov, Tanmay Kulshrestha, Ken Wing-Kin Sung, Anders Jacobsen Skanderup
Summary: PUREE is a weakly supervised machine learning algorithm that accurately infers tumor purity from bulk tumor gene expression data. It can predict purity with high accuracy across different solid tumor types and is applicable to tumor samples from unseen tumor types and cohorts. In a comprehensive benchmark, PUREE outperforms existing transcriptome-based purity estimation approaches.
COMMUNICATIONS BIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Markus Pfenninger, Philipp Schoennenbeck, Tilman Schell
Summary: Accurate estimation of genome sizes is essential in biodiversity genomics, and this study introduces a method that can estimate genome size from the number of sequenced bases and mean sequencing depth. Simulations demonstrate that even from low-coverage genome drafts, reasonable estimates can be obtained using this method. Comparison with flow cytometry estimates suggests that both methods provide similar and interchangeable results.
MOLECULAR ECOLOGY RESOURCES
(2022)
Article
Biochemistry & Molecular Biology
Zilong Li, Jonas Meisner, Anders Albrechtsen
Summary: Principal component analysis (PCA) is widely used for dimensionality reduction and uncovering latent structure in statistics, machine learning, and genomics. To address the challenges of ever-growing data, this paper proposes a novel algorithm called PCAone, which achieves fast and memory-efficient PCA and outperforms existing methods in comprehensive evaluations using multiple large-scale real-world datasets.
Article
Forestry
Chandan Kumar, Steven Psaltis, Henri Bailleres, Ian Turner, Loic Brancheriau, Gary Hopewell, Elliot J. Carr, Troy Farrell, David J. Lee
Summary: A novel non-destructive method has been developed to predict modulus of elasticity (MOE) of logs using measurements taken from cores extracted from discs. The method shows that a single core from breast height is sufficient to predict MOE of logs, allowing early grading and sorting of logs for optimal use and processing. The integral average method predicted the BING-MOE more accurately with lower bias compared with other existing tools without any complex equipment, analysis, and statistical calibration for segregating out individual trees or stands.
ANNALS OF FOREST SCIENCE
(2021)
Correction
Forestry
Chandan Kumar, Steven Psaltis, Henri Bailleres, Ian Turner, Loic Brancheriau, Gary Hopewell, Elliot J. Carr, Troy Farrell, David J. Lee
Summary: The incorrect affiliation details for co-author David J. Lee in the original article have been corrected to Forest Industries Research Centre, University of the Sunshine Coast, Australia.
ANNALS OF FOREST SCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Daniel Laidig, Thomas Seel
Summary: The miniaturization of MEMS-based IMUs has made them widely used in various applications. Orientation estimation is a fundamental sensor fusion task for inertial motion tracking, and the accuracy of estimated orientations affects further data processing steps. This study proposes a quaternion-based orientation estimation algorithm that outperforms existing methods and achieves improved accuracy across different motion characteristics.
INFORMATION FUSION
(2023)
Article
Biochemical Research Methods
Maya Gupta, Paul Zaharias, Tandy Warnow
Summary: BAli-Phy, originally designed for co-estimation of multiple sequence alignments and phylogenetic trees, has been repurposed as a 'phylogeny-aware' alignment method in this study. By utilizing estimated phylogenies as fixed trees, the approach achieves higher accuracy than Prank and even outperforms MAFFT, allowing for alignment of large datasets up to 1000 sequences.
Article
Economics
Feng Chen, Chang-Lin Mei
Summary: An adaptive scale method is proposed to improve the estimation accuracy of mixed GWR models and provide valuable information on the operating scale of explanatory variables.
ECONOMIC MODELLING
(2021)
Article
Engineering, Electrical & Electronic
Haoqian Wang, Xiaowan Hu, Xiaole Zhao, Yulun Zhang
Summary: The paper proposes a wide weighted attention multi-scale network (W(2)AMSN) for accurate MR image super-resolution (SR). The network extracts features of varying sizes and recalibrates feature responses using a non-reduction attention mechanism. The method also selectively fuses the extracted features using learnable weighted factors. Extensive experiments show the effectiveness of the proposed method.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Biotechnology & Applied Microbiology
Scott Hotaling, Edward R. Wilcox, Jacqueline Heckenhauer, Russell J. Stewart, Paul B. Frandsen
Summary: Highly accurate long-reads generated with HiFi or analogous technologies are crucial for improving genome assembly quality in plants and animals, especially when resources limit the choice to one type of sequencing data.
Article
Evolutionary Biology
Ishrat Tanzila Farah, Muktadirul Islam, Kazi Tasnim Zinat, Atif Hasan Rahman, Shamsuzzoha Bayzid
Summary: Estimating species trees from multilocus data sets is challenging due to gene tree heterogeneity caused by incomplete lineage sorting. Summary methods combine gene trees to estimate a species tree by optimizing various scores. This study explores the presence and impacts of equally optimal trees in species tree estimation using methods that consider incomplete lineage sorting. The experiment indicates that one method, MDC, may result in competitive quartet consistency scores but worse tree accuracy compared to another method, MQC, demonstrating the importance of considering equally optimal species trees in phylogenomic inference using summary methods.
SYSTEMATIC BIOLOGY
(2021)
Article
Evolutionary Biology
Tom A. Williams, Adrian A. Davin, Benoit Morel, Lenard L. Szantho, Anja Spang, Alexandros Stamatakis, Philip Hugenholtz, Gergely J. Szollosi
Summary: ALE and GeneRax are reliable methods for probabilistic gene tree-species tree reconciliation. They accurately infer gene duplication, transfer, and loss events based on gene vs. species tree discordance. These methods have been used to root species trees and infer ancestral gene repertoires. While there have been criticisms of their reliability, our assessment shows that they are accurate when applied to simulated data and are generally in agreement with alternative methodological approaches on empirical data. ALE and related approaches are promising tools for studying genome evolution.
GENOME BIOLOGY AND EVOLUTION
(2023)
Article
Multidisciplinary Sciences
Romane Gauriau, Bernardo C. Bizzo, Donnella S. Comeau, James M. Hillis, Christopher P. Bridge, John K. Chin, Jayashri Pawar, Ali Pourvaziri, Ivana Sesic, Elshaimaa Sharaf, Jinjin Cao, Flavia T. C. Noro, Walter F. Wiggins, M. Travis Caton, Felipe Kitamura, Keith J. Dreyer, John F. Kalafut, Katherine P. Andriole, Stuart R. Pomerantz, Ramon G. Gonzalez, Michael H. Lev
Summary: Non-contrast head CT is not sensitive for early acute infarct identification. We developed a deep learning model that detects and delineates suspected early infarcts on NCCT using diffusion MRI as ground truth. The model outperformed expert neuroradiologists in sensitivity and specificity for detecting stroke, and showed strong correlation with diffusion MRI for infarct volume estimation.
SCIENTIFIC REPORTS
(2023)
Article
Nuclear Science & Technology
Md. Saifur Rahman, M. A. Malek Soner, M. Mizanur Rahman, Md. Al Amin Hossain, M. A. Salam, M. N. A. Abdullah
ANNALS OF NUCLEAR ENERGY
(2019)
Article
Computer Science, Artificial Intelligence
M. Saifur Rahman, Md. Khaledur Rahman, Sanjay Saha, M. Kaykobad, M. Sohel Rahman
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2019)
Article
Engineering, Biomedical
Nabil Ibtehaz, M. Saifur Rahman, M. Sohel Rahman
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2019)
Article
Computer Science, Artificial Intelligence
Nabil Ibtehaz, M. Sohel Rahman
Article
Biochemical Research Methods
Mostofa Rafid Uddin, Sazan Mahbub, M. Saifur Rahman, Md Shamsuzzoha Bayzid
Article
Biochemical Research Methods
Ali Haisam Muhammad Rafid, Md. Toufikuzzaman, Mohammad Saifur Rahman, M. Sohel Rahman
BMC BIOINFORMATICS
(2020)
Article
Biochemical Research Methods
Mujtahid Akon, Muntashir Akon, Mohimenul Kabir, M. Saifur Rahman, M. Sohel Rahman
Summary: This research focuses on developing an alignment-free framework for analyzing biological sequences and introduces the Alignment-free Dissimilarity Analysis & Comparison Tool (ADACT), which aims to simplify the workflow for researchers and practitioners in the field of bioinformatics.
Article
Radiology, Nuclear Medicine & Medical Imaging
Iram Tazim Hoque, Nabil Ibtehaz, Saumitra Chakravarty, M. Saifur Rahman, M. Sohel Rahman
Summary: The proposed approach based on contour properties for segmentation of nuclei in cervical cytology pap smear images has shown superior performance in automated cervical cancer screening. The method outperforms other state-of-the-art methods in nucleus segmentation, with high precision and recall on both benchmark and private real datasets. The flexibility of the algorithm to adapt to real practical scenarios and requirements makes it a promising tool for effective detection and segmentation of nuclei.
BMC MEDICAL IMAGING
(2021)
Article
Geosciences, Multidisciplinary
Rashed Uz Zzaman, Sara Nowreen, Irtesam Mahmud Khan, Md Rajibul Islam, Nabil Ibtehaz, M. Saifur Rahman, Anwar Zahid, Dilruba Farzana, Afroza Sharmin, M. Sohel Rahman
Summary: This study introduces a methodology utilizing machine learning to assess the suitability of groundwater extraction technologies in different regions of Bangladesh, highlighting key hydrogeological factors. The research demonstrates that the Random Forest algorithm is the optimal classification model, also identifying digital elevation model, specific yield, and lithology as the most influential factors on groundwater levels in Bangladesh.
NATURAL RESOURCES RESEARCH
(2022)
Article
Biology
Muhammad Ali Nayeem, Md. Shamsuzzoha Bayzid, Naser Anjum Samudro, M. Saifur Rahman, M. Sohel Rahman
Summary: This paper introduces the application of the PASTA method in multiple sequence alignment and proposes a multi-objective framework called PMAO to improve the performance of PASTA by integrating multiple objectives related to the accuracy of the phylogenetic tree. Experimental results show that the tree-space generated by PMAO is better than using PASTA alone, and adding an additional component can generate smaller and higher quality solutions.
COMPUTATIONAL BIOLOGY AND CHEMISTRY
(2022)
Article
Biochemical Research Methods
Muhammad Ali Nayeem, Naser Anjum Samudro, M. Saifur Rahman, M. Sohel Rahman
Summary: In this study, a framework called MAMMLE is proposed to infer better phylogenetic trees from unaligned sequences by hybridizing two MSA tools (MUSCLE and MAFFT) with multiobjective optimization strategy and multiple maximum likelihood hypotheses. Experimental results show that MAMMLE exhibits a median improvement of 5.57% over MUSCLE in 50.34% of instances.
JOURNAL OF COMPUTATIONAL BIOLOGY
(2023)
Article
Medical Informatics
Junaed Younus Khan, Tawkat Islam Khondaker, Iram Tazim Hoque, Hamada R. H. Al-Absi, Mohammad Saifur Rahman, Reto Guler, Tanvir Alam, M. Sohel Rahman
JMIR MEDICAL INFORMATICS
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Muhammad Ali Nayeem, Md. Shamsuzzoha Bayzid, Atif Hasan Rahman, Rifat Shahriyar, M. Sohel Rahman
PROCEEDINGS OF THE 2019 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'19)
(2019)
Proceedings Paper
Computer Science, Information Systems
Ahmad S. Tarawneh, Ahmad B. Hassanat, Ceyhun Celik, Dmitry Chetverikov, M. Sohel Rahman, Chaman Verma
2019 10TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS (ICICS)
(2019)