Article
Biochemical Research Methods
Jie Huang, Stefano Pallotti, Qianling Zhou, Marcus Kleber, Xiaomeng Xin, Daniel A. King, Valerio Napolioni
Summary: The development of PERHAPS allows for direct calling of haplotypes from short-read, paired-end NGS data with high reliability. By applying this method, the study successfully extracted haplotype data related to APOE polymorphism and identified the rare APOE(*)1 haplotype in the African population.
BRIEFINGS IN BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Wei Zhang, Jia Ju, Yong Zhou, Teng Xiong, Mengyao Wang, Chaohui Li, Shixin Lu, Zefeng Lu, Liya Lin, Xiao Liu, Shuai Cheng Li
Summary: The Adaptive Immune Receptor Repertoire (AIRR) is crucial in cancer immunotherapy and MRD detection. A software package called IMperm was developed to efficiently merge PE reads, successfully handling low-quality and non-overlapping reads. Compared to existing tools, IMperm showed better performance in both simulated and sequencing data, and also demonstrated its effectiveness in handling PE reads from other sources.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Xiguo Yuan, Wenlu Xie, Hongzhi Yang, Jun Bai, Ruwu Yang, Guojun Liu, Haque A. K. Alvi
Summary: Interspersed duplicated insertion (idINS) is a common type of genomic insertion that plays a significant role in genomic instability and cancer genesis. The novel algorithm DIPins accurately detects and infers idINS contents from paired-end reads, even when the variation exceeds the insert size. DIPins shows advantages over existing methods and has potential for accurate characterization of idINSs in the human genome.
DIGITAL SIGNAL PROCESSING
(2021)
Article
Biochemical Research Methods
Weizhi Song, Shan Zhang, Torsten Thomas
Summary: This study developed a tool called MarkerMAG that links 16S rRNA genes to metagenome-assembled genomes (MAGs) using paired-end sequencing reads. Evaluation on multiple datasets showed that MarkerMAG significantly increases the number of MAGs with 16S rRNA genes and accurately assigns and estimates their copy number. MarkerMAG-improved MAGs also enhance the accuracy of functional prediction from 16S rRNA gene amplicon data.
Article
Biochemical Research Methods
Daniel P. Dacey, Frederic J. J. Chain
Summary: The study revealed that combining unmerged concatenated reads with merged sequences enhances the performance of taxonomic classification, particularly in mock communities with larger amplicons. Different trimming parameters and reference databases have varying effects on the accuracy of genus level classification.
BMC BIOINFORMATICS
(2021)
Article
Agronomy
Myung-Shin Kim, Hojin Jo, Ji Hong Kim, Dong Nyuk Bae, In-Soon Pack, Chang-Gi Kim, Tackmin Kwon, Jaesung Nam, Young-Soo Chung, Soon-Chun Jeong
Summary: The study established an analysis pipeline for identifying transgene insertion sites in transgenic soybean by de novo genome assembly using high-throughput sequencing data. The integration site sequences near three annotated genes were confirmed against the soybean reference genome and PCR amplification, revealing precise transgene-flanking sequences and sequence rearrangements. This approach proved to be straightforward and time-effective, providing an alternative method for identifying insertion sites in transgenic plants compared to experimental or enrichment technologies.
MOLECULAR BREEDING
(2021)
Article
Genetics & Heredity
Midhuna Immaculate, Joseph Maran, Dicky John G. Davis
Summary: This study compares and evaluates different preprocessing and merging methods for eDNA data, and finds that direct merging with the FLASH tool can better preserve reads without the need for strict quality trimming. The results suggest that merging paired-end reads of eDNA data before quality trimming can help conserve more reads.
Article
Multidisciplinary Sciences
Fanny-Dhelia Pajuste, Maido Remm
Summary: The study developed a computational method GeneToCN that can infer gene copy number based on gene-specific k-mer frequencies. The method was validated using experimental data and showed strong correlation with experimentally determined copy numbers. Additionally, the method showed good agreement with previous studies and performed consistently across different sequencing technologies.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Interdisciplinary Applications
Yihui Liang, Shuang Zou, Caijin Xie
Summary: In this paper, a numerical method called the parameter space reconstruction method is proposed to address four critical problems in the numerical modeling of rock-filled concrete. This method efficiently generates a high rockfill ratio model, forms a rock skeleton, generates the interfacial transition zone, and ensures the operability of the model. The accuracy of this method is verified through uniaxial compressive strength simulations, showing good agreement with experimental results.
COMPUTERS & STRUCTURES
(2023)
Article
Engineering, Aerospace
Shaochen Li, Hailong Tang, Min Chen
Summary: This study introduces a new method to accurately correct engine component maps over a wide range, ensuring high accuracy, and validates the effectiveness of this method through an example.
CHINESE JOURNAL OF AERONAUTICS
(2021)
Article
Automation & Control Systems
Zihan Li, Dong Shen
Summary: Existing parameter estimation methods for continuous-time systems have limitations such as slow convergence, the requirement of specific excitation conditions, and the inability to estimate fast-changing parameters. This study proposes a new filter-free estimation method that has faster convergence, does not require specific excitation conditions, and can estimate fast-changing parameters.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Chemistry, Medicinal
Ebru Akkus, Omer Tayfuroglu, Muslum Yildiz, Abdulkadir Kocak
Summary: In this paper, a new strategy is introduced to estimate binding free energies using end-state molecular dynamics simulation trajectories. The method, based on linear interaction energy (LIE) and ANI-2x neural network potentials (machine learning), predicts the single-point interaction energies between ligand-protein and ligand-solvent pairs with high accuracy. Experimental results show that the method outperforms current end-state methods, while having reduced computational cost. It also allows for comparison of binding free energies between ligands with different scaffolds.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Environmental Sciences
Muhittin Ozan Karaman, Saye Nihan Cabuk, Emrah Pekkan
Summary: Geographical information systems (GIS) were used to create landslide susceptibility maps in the Karaburun Peninsula in Izmir. This study provides important inputs for sustainable planning in the region.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Xuelong Li, Han Zhang, Rong Wang, Feiping Nie
Summary: This paper presents a scalable and parameter-free graph fusion framework for multiview clustering, seeking a joint graph compatible across multiple views in a self-supervised weighting manner. The method overcomes common issues such as intractable hyper-parameters and time overheads, and exhibits good initialization independence and time economy. Experimental results demonstrate the superiority of the proposed method in terms of clustering performance and time expenditure compared to existing methods.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Engineering, Aerospace
Qingliang Meng, Dapeng Han, Zhaokui Wang
Summary: This paper proposes a model-free method for determining the attitude and inertial parameters of a noncooperative target by sequentially registering point clouds captured by a depth camera. The method combines the multiplicative extended Kalman filter and pose graph optimization to reduce measurement noise and drift error. Experimental results confirm the superiority of this method in identifying inertial parameters and its effectiveness in avoiding registration ambiguity.
ADVANCES IN SPACE RESEARCH
(2023)
Article
Biochemical Research Methods
Md Abid Hasan, Stefano Lonardi
BMC BIOINFORMATICS
(2020)
Article
Biochemical Research Methods
Dipankar Ranjan Baisya, Stefano Lonardi
Article
Microbiology
Ashley E. Braddom, Sebastiaan Bol, S. Jake Gonzales, Raphael A. Reyes, Kenneth Musinguzi, Felistas Nankya, Isaac Ssewanyana, Bryan Greenhouse, Evelien M. Bunnik
Summary: This study compared B cells in adults with and without experience of malaria and found that Plasmodium exposure mainly affects changes in atMBCs, with IgM(+) and IgG(+) atMBCs being distinct populations that should be analyzed separately. Regardless of Plasmodium exposure, IgM(+) atMBCs resembled NBCs, while IgG(+) atMBCs resembled IgG(+) cMBCs.
Article
Biochemical Research Methods
Qihua Liang, Stefano Lonardi
Summary: PGV is a reference-agnostic representation of a species' pan-genome based on consensus ordering, enabling intuitive, effective, and interactive visualization of complex structural genomic variations. The PGV software can be easily installed via conda or downloaded from the website, with a companion browser available for testing using example bed tracks from the GitHub page.
BMC BIOINFORMATICS
(2021)
Article
Infectious Diseases
S. Jake Gonzales, Sebastiaan Bol, Ashley E. Braddom, Richard Sullivan, Raphael A. Reyes, Isaac Ssewanyana, Erica Eggers, Bryan Greenhouse, Evelien M. Bunnik
Summary: The study found that following a malaria episode, the expression of FcRL5 increased in various atypical MBC subsets, with the highest expression observed in IgG(+) atypical MBCs. IgM(+) atypical MBCs showed fewer connections with other B cell subsets, while IgG(+) atypical MBCs were clonally expanded and connected with classical MBCs.
Article
Multidisciplinary Sciences
Raphael A. Reyes, Kathleen Clarke, S. Jake Gonzales, Angelene M. Cantwell, Rolando Garza, Gabriel Catano, Robin E. Tragus, Thomas F. Patterson, Sebastiaan Bol, Evelien M. Bunnik
Summary: The research found subtle differences in the memory B cell response after non-severe and severe COVID-19, indicating that the memory B cell response elicited during non-severe COVID-19 may be of higher quality than the response after severe disease.
Article
Multidisciplinary Sciences
Dipankar Baisya, Adithya Ramesh, Cory Schwartz, Stefano Lonardi, Ian Wheeldon
Summary: In this paper, the authors propose a neural network-based architecture called DeepGuide, which learns from genome-wide CRISPR activity profiles to accurately design high activity sgRNAs. The experimental validation confirms the effectiveness of DeepGuide in predicting high activity sgRNAs in the oleaginous yeast Yarrowia lipolytica.
NATURE COMMUNICATIONS
(2022)
Article
Biology
Sebastiaan Bol, Adrian Scaffidi, Evelien M. Bunnik, Gavin R. Flematti
Summary: This study found that besides catnip, several other plants can also elicit a euphoric response in cats. Individual differences in cats can affect their response to these plants, but the behavior of individual cats is consistent across all plants. Additionally, a new compound that can elicit the catnip response was discovered.
Article
Plant Sciences
Qihua Liang, Maria Munoz-Amatriain, Shengqiang Shu, Sassoum Lo, Xinyi Wu, Joseph W. Carlson, Patrick Davidson, David M. Goodstein, Jeremy Phillips, Nadia M. Janis, Elaine J. Lee, Chenxi Liang, Peter L. Morrell, Andrew D. Farmer, Pei Xu, Timothy J. Close, Stefano Lonardi
Summary: In this study, de novo genome assemblies were produced for representatives of six subpopulations of cultivated cowpea to capture the genomic diversity of this important legume. Core genes were found to be enriched in transcription factor activity, and transport and metabolic processes, while noncore genes were enriched in response to stress and defense response. Additionally, over 5 million single nucleotide polymorphisms (SNPs) and over 40 structural variants >1 Mb in size were identified through genome comparisons. Noncore genes were found to harbor a larger proportion of potentially disruptive variants, indicating their substantial contribution to diversity within domesticated cowpea.
Article
Microbiology
Pallavi Singh, Stefano Lonardi, Qihua Liang, Pratap Vydyam, Eleonora Khabirova, Tiffany Fang, Shalev Gihaz, Jose Thekkiniath, Muhammad Munshi, Steven Abel, Loic Ciampossin, Gayani Batugedara, Mohit Gupta, Xueqing Maggie Lu, Todd Lenz, Sakshar Chakravarty, Emmanuel Cornillot, Yangyang Hu, Wenxiu Ma, Luis Miguel Gonzalez, Sergio Sanchez, Karel Estrada, Alejandro Sanchez-Flores, Estrella Montero, Omar S. Harb, Karine G. Le Roch, Choukri Ben Mamoun
Summary: Babesia duncani is a tick-transmitted pathogen causing a malaria-like disease in humans and animals. This study provides a comprehensive analysis of its molecular biology, genomics, transcriptomics, and epigenetics. The identification of candidate virulence factors, diagnostic antigens, and potential drug targets in the genome, epigenome, and transcriptome of B. duncani could lead to the development of effective therapies for human babesiosis.
NATURE MICROBIOLOGY
(2023)
Article
Biology
Adithya Ramesh, Varun Trivedi, Sangcheon Lee, Aida Tafrishi, Cory Schwartz, Amirsadra Mohseni, Mengwan Li, Stefano Lonardi, Ian Wheeldon
Summary: acCRISPR is a method that corrects the inaccuracies in CRISPR screening results caused by variability in sgRNA cutting efficiency by computing a fitness score for each targeted gene. It is used to identify essential genes and their fitness effects in CRISPR screens. The study applied acCRISPR to identify essential genes for growth under glucose and salt tolerance conditions in the yeast Yarrowia lipolytica. This work presents an experimental-computational framework for CRISPR-based functional genomics studies in non-conventional organisms.
COMMUNICATIONS BIOLOGY
(2023)
Article
Microbiology
James L. McLellan, William Sausman, Ashley B. Reers, Evelien M. Bunnik, Kirsten K. Hanson
Summary: Researchers have developed a new assay to detect translation inhibition in the liver stage of Plasmodium parasites and identified a potential antimalarial drug.
Article
Genetics & Heredity
Saleh Sereshki, Nathan Lee, Michalis Omirou, Dionysia Fasoula, Stefano Lonardi
Summary: DNA methylation can be detected and measured using sequencing instruments after sodium bisulfite conversion, but experiments can be expensive for large eukaryotic genomes. Several computational methods have been proposed to predict DNA methylation from the DNA sequence or nearby methylation levels, but most are focused on CG methylation in humans and other mammals. In this study, we investigate the prediction of cytosine methylation in plant species and introduce a new classifier, AMPS, that utilizes genomic annotations to improve prediction accuracy.
NAR GENOMICS AND BIOINFORMATICS
(2023)
Article
Biotechnology & Applied Microbiology
Abbas Roayaei Ardakany, Halil Tuvan Gezer, Stefano Lonardi, Ferhat Ay
Article
Biochemical Research Methods
Weihua Pan, Tao Jiang, Stefano Lonardi
JOURNAL OF COMPUTATIONAL BIOLOGY
(2020)