Article
Biochemical Research Methods
Fatemeh Farhadi, Mohammad Allahbakhsh, Ali Maghsoudi, Nadieh Armin, Haleh Amintoosi
Summary: In this research, a computational approach called DiMo is proposed for identifying motifs in microRNAs and macromolecules of small length. Word embedding techniques and deep learning models are utilized to improve the accuracy of motif discovery, and transfer learning models are employed in cases of limited training data. Compared to five state-of-the-art works using real-world datasets, DiMo outperforms in terms of precision, recall, accuracy, and f1-score.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Biochemical Research Methods
Rahul Semwal, Imlimaong Aier, Utkarsh Raj, Pritish Kumar Varadwaj
Summary: In this study, a k-mer based motif discovery approach called Pr[m] is proposed for detecting statistically significant motif patterns in protein sequences. Comparative analysis with existing methods showed that Pr[m] outperforms in predictive quality and performance.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Chemistry, Analytical
Qingxia Yang, Yaguo Gong, Feng Zhu
Summary: Multiclass metabolomics is widely used in clinical practice for understanding disease progression and identifying diagnostic biomarkers. It is more challenging than the binary problem due to the complexity of determining class decision boundaries. However, there is still a lack of a systematic assessment for selecting appropriate methods in multiclass metabolomics.
ANALYTICAL CHEMISTRY
(2023)
Review
Biochemical Research Methods
Stefano Castellana, Tommaso Biagini, Luca Parca, Francesco Petrizzelli, Salvatore Daniele Bianco, Angelo Luigi Vescovi, Massimo Carella, Tommaso Mazza
Summary: This study found that hundreds of human proteins interact with degenerated DNA sequences, and identifying these motifs and genomic sites is a challenging research goal in modern molecular biology and bioinformatics. Over the past twenty years, there has been an explosion of computational tools for this task, and sixteen of them were evaluated for their ability to identify known motifs in simulated sequence datasets.
BRIEFINGS IN BIOINFORMATICS
(2021)
Review
Construction & Building Technology
Najmeh Cheraghi-Shirazi, Keith Crews, Sardar Malek
Summary: Human comfort is an important requirement for timber floors, but there is no consensus on the applicability of existing design methods to timber composite floors. Vibration is a major challenge in achieving longer spans with steel-timber composite floors, and the suitable vibration criteria vary depending on the weight of the composite floor. Accurate estimation of connection stiffness and damping ratio is recommended for detailed numerical analysis.
Article
Biochemical Research Methods
Mohammad Vahed, Majid Vahed, Lana X. Garmire
Summary: Motif discovery and characterization are crucial for gene regulation analysis, but the lack of intuitive and integrative web servers hinders the effective use of motifs. BML, a parameter-free web server, offers a user-friendly portal for online discovery and analysis of sequence motifs, achieving higher accuracy than other available tools.
BRIEFINGS IN BIOINFORMATICS
(2022)
Review
Chemistry, Multidisciplinary
Wai Cheung Chan, Shabnam Sharifzadeh, Sara J. Buhrlage, Jarrod A. Marto
Summary: Covalent drugs are essential in modern medicine, and there has been a recent surge in interest in the development of covalent inhibitors, particularly utilizing mass spectrometry-based chemoproteomic methods. This review highlights the practical applications of these techniques in target identification, hit discovery, and lead characterization/optimization in covalent drug discovery, with case studies to demonstrate their real-world significance and future opportunities.
CHEMICAL SOCIETY REVIEWS
(2021)
Article
Biochemistry & Molecular Biology
Lingyu Guan, Vincent Lam, Andrey Grigoriev
Summary: This study identified potential interaction regions of tRNA-derived fragments (tRFs) on a larger scale and proposed a novel model connecting the formation of asymmetric pairs and the potential binding mechanisms of tRFs. The findings suggest a way forward for further experimental elucidation of tRF-binding mechanisms.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2021)
Article
Computer Science, Information Systems
M. Van Onsem, V. Ledoux, W. Melange, D. Dreesen, S. Van Hoecke
Summary: This paper proposes a variable length motif discovery method based on the Matrix Profile, which focuses on industrial applicability. The method can find both short and long motifs in the same time series, works in noisy and periodic environments, and only requires one distance matrix calculation.
Article
Computer Science, Artificial Intelligence
Guojiang Shen, Difeng Zhu, Jingjing Chen, Xiangjie Kong
Summary: With the development of intelligent transportation systems, clustering methods have gained significant attention for traffic pattern recognition in road networks. However, the complex relationships among different segments in road networks have been overlooked. To address this issue, this study proposes a clustering method for motif-based attributed road networks and demonstrates its superiority through experiments.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Biochemical Research Methods
Mahdi Pursalim, Kwoh Chee Keong
Summary: This paper presents a motif localization method based on a novel clustering algorithm in complex networks, which speeds up motif discovery by generating an Augmented Multiresolution Network and adaptively partitioning subnets. Experimental results show efficient handling of complex networks representing large datasets with high-dimensionality, providing motivation for future studies in big data and complex networks.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Biochemical Research Methods
Yuanfang Ren, Aisharjya Sarkar, Pierangelo Veltri, Ahmet Ay, Alin Dobra, Tamer Kahveci
Summary: This study addresses the problem of counting instances of user-supplied motif topologies in multilayer networks, modeling interactions among entities under varying conditions or time variations. The developed algorithm showed high accuracy and speed advantages compared to existing methods when applied to synthetic and real datasets.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Medicine, Research & Experimental
Vu Viet Hoang Pham, Lin Liu, Cameron Bracken, Gregory Goodall, Jiuyong Li, Thuc Duy Le
Summary: Researchers conducted a comprehensive review of computational methods for discovering cancer drivers, categorizing them into three groups and evaluating their performance in identifying biologically significant cancer drivers to provide readers with information.
Article
Mathematics, Applied
Rachael T. Keller, Qiang Du
Summary: This study investigates the application of linear multistep methods in learning dynamics, establishing a rigorous framework for convergence in the discovery problem and indicating convergence conditions for several M-step LMMs schemes. Additionally, numerical experiments are provided to support the theoretical analysis.
SIAM JOURNAL ON NUMERICAL ANALYSIS
(2021)
Article
Computer Science, Artificial Intelligence
Fabian Kai-Dietrich Noering, Yannik Schroeder, Konstantin Jonas, Frank Klawonn
Summary: This paper evaluates different approaches for discovering frequent variable-length patterns in time series, including techniques such as Convolutional Autoencoder and Dynamic Time Warping. The experiment shows that Convolutional Autoencoders have the ability to discover patterns with a similar quality as classical nonlearning approaches.
INTEGRATED COMPUTER-AIDED ENGINEERING
(2021)
Article
Immunology
M. Fleur du Pre, Jana Blazevski, Alisa E. Dewan, Jorunn Stamnaes, Chakravarthi Kanduri, Geir Kjetil Sandve, Marie K. Johannesen, Christian B. Lindstad, Kathrin Hnida, Lars Fugger, Gerry Melino, Shuo-Wang Qiao, Ludvig M. Sollid
JOURNAL OF EXPERIMENTAL MEDICINE
(2020)
Article
Biochemical Research Methods
Rezvan Ehsani, Finn Drablos
BMC BIOINFORMATICS
(2020)
Article
Multidisciplinary Sciences
Ashish Kumar Singh, Bente Talseth-Palmer, Mary McPhillips, Liss Anne Solberg Lavik, Alexandre Xavier, Finn Drablos, Wenche Sjursen
Editorial Material
Biochemical Research Methods
Gabriel Balaban, Ivar Grytten, Knut Dagestad Rand, Lonneke Scheffer, Geir Kjetil Sandve
PLOS COMPUTATIONAL BIOLOGY
(2021)
Article
Genetics & Heredity
Kjersti Rise, May-Britt Tessem, Finn Drablos, Morten B. Rye
Summary: Cytoscape is commonly used for visualization and analysis of metabolic pathways, but interpreting pathways based on KEGG data can be challenging. FunHoP is a new method that shows all possible genes in each node, making the pathways more complete and providing more consistent biological interpretations of metabolic pathways.
GENOMICS PROTEOMICS & BIOINFORMATICS
(2021)
Article
Biochemical Research Methods
Torbjorn Rognes, Lonneke Scheffer, Victor Greiff, Geir Kjetil Sandve
Summary: In this study, CompAIRR was developed for fast computation of AIRR overlap, achieving a 1000-fold improvement in computational speed compared to existing methods. CompAIRR has been integrated with immuneML, a machine learning ecosystem for AIRR analysis.
Letter
Biochemical Research Methods
Geir Kjetil Sandve, Victor Greiff
Article
Multidisciplinary Sciences
Kjersti Rise, May-Britt Tessem, Finn Drablos, Morten Beck Rye
Summary: This study expands a method for analyzing functional homologous proteins, which can differentiate between mitochondrial and non-mitochondrial processes in cancer cells and normal cells. The results show that mitochondrial pathways are upregulated in prostate cancer.
Article
Multidisciplinary Sciences
Marketa Chlubnova, Asbjorn O. Christophersen, Geir Kjetil F. Sandve, Knut E. A. Lundin, Jorgen Jahnsen, Shiva Dahal-Koirala, Ludvig M. Sollid
Summary: 42 wheat gluten-reactive T cell clones with different phenotypes and no reactivity to known epitopes were screened. Synthetic peptides were identified bioinformatically from a wheat gluten protein database and tested against the T cell clones. Reactivity of 10 T cell clones was assigned, and 5 previously uncharacterized gliadin/glutenin epitopes with a 9-nucleotide oligomer core region were identified. This work represents an advance in identifying CeD-driving gluten epitopes.
Article
Psychiatry
Emilie Willoch Olstad, Hedvig Marie Egeland Nordeng, Geir Kjetil Sandve, Robert Lyle, Kristina Gervin
Summary: This study investigated the associations between prenatal exposure to citalopram or escitalopram, maternal depression, and offspring DNA methylation (DNAm). The researchers also examined the interaction effect of (es)citalopram exposure and DNAm on neurodevelopmental outcomes, as well as the correlation between DNAm at birth and neurodevelopmental trajectories in childhood.
TRANSLATIONAL PSYCHIATRY
(2023)
Article
Computer Science, Artificial Intelligence
Mai Ha Vu, Rahmad Akbar, Philippe A. Robert, Bartlomiej Swiatczak, Geir Kjetil Sandve, Victor Greiff, Dag Trygve Truslew Haug
Summary: Language models trained on proteins can predict functions from sequences but lack insight into underlying mechanisms. Extracting rules from these models can make them interpretable and help explain biological mechanisms.
NATURE MACHINE INTELLIGENCE
(2023)
Article
Biochemical Research Methods
Ping-Han Hsieh, Camila Miranda Lopes-Ramos, Manuela Zucknick, Geir Kjetil Sandve, Kimberly Glass, Marieke Lydia Kuijjer
Summary: Gene co-expression measurements are widely used in computational biology to identify coordinated expression patterns. However, certain normalization methods can introduce false-positive associations between genes, hindering downstream co-expression network analysis. In this study, a normalization method called SNAIL (Smooth-quantile Normalization Adaptation for the Inference of co-expression Links) is developed to avoid false-positive associations and retain associations to genes expressed in small subgroups of samples. This method has the potential to impact network modeling and association-based approaches in large-scale heterogeneous data.
Article
Biology
Chakravarthi Kanduri, Milena Pavlovic, Lonneke Scheffer, Keshav Motwani, Maria Chernigovskaya, Victor Greiff, Geir K. Sandve
Summary: This article presents a study aimed at determining the effectiveness of baseline machine learning (ML) methods in the classification of adaptive immune receptor repertoires (AIRRs). The study generated a series of synthetic AIRR benchmark datasets and found that even when the immune signal occurs only in 1 out of 50,000 AIR sequences, the baseline L1-penalized logistic regression model can achieve high prediction accuracy.
Article
Biology
Casper van Mourik, Rezvan Ehsani, Finn Drablos
Summary: Gene products can be described using GO terms, but for many genes the information about their products, especially lncRNAs, is limited. GAPGOM integrates two algorithms for annotation prediction and similarity estimation between GO graphs, providing improved performance and additional features.
BMC RESEARCH NOTES
(2021)
Article
Oncology
Rezvan Ehsani, Finn Drablos
CANCER INFORMATICS
(2020)