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Science 2025年第6740期387卷 1261页

作者： Dov Greenbaum Mark Gerstein The reviewer is at the Zvi Meitar Institute for Legal Implications of Emerging Technologies The reviewer is at the Harry Radzyner Law School The reviewer is at the Dina Recanati School of Medicine Reichman University Herzliya Israel The reviewer is at the Department of Biomedical Informatics and Data Science The reviewer is at the Program in Computational Biology and Bioinformatics The reviewer is at the Department of Computer Science Yale University New Haven CT USA.

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Representational momentum may explain aspects of vowel shifts

Representational momentum may explain aspects of vowel shift...

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13th International Conference on the Simulation and Synthesis of Living Systems: Artificial Life 13, ALIFE 2012

作者： Swarup, Samarth McCarthy, Corrine Virginia Bioinformatics Institute Virginia Tech. Blacksburg VA 24061 United States Linguistics Program Department of English George Mason University Fairfax VA 22030 United States

ISBN: (纸本)9780262310505

We present a computational model of vowel shifts, applied in particular to the Northern Cities Vowel Shift. Our model incorporates several empirically-derived rules of vowel change. The key aspect of this model is the use of representational momentum, which, we argue, explains multiple observed features of the shift. We compare our model with data on the Northern Cities Shift spanning more than a century and show that, when representational momentum is included, the results of the model match the data well. © 2012 Massachusetts Institute of Technology.

关键词： Linguistics

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Exploring EfficientNet Variants for Image Encoding in Auxiliary Signal Guided Knowledge Encoder-Decoder Framework 9th

Exploring EfficientNet Variants for Image Encoding in Auxili...

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9th International Conference on Computer Science and Computational Intelligence, ICCSCI 2024

作者： Henry, Matthew Martianus Heryanto, Nur Adhianti Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

The growing number of medical images has led to radiologist burnout, which seriously impacts the radiologist's performance. To address the previously mentioned issue, an Auxiliary Signal Guided Knowledge (ASGK) multimodal encoder-decoder framework was designed to automatically generate the medical report based on the proposed medical graph and natural language decoder. It utilizes DenseNet-121 as the image encoder. With DenseNet-121 lack of computational and memory efficiency, this study aims to explore the potential of EfficientNetB0 to EfficientNetB4 as an ASGK image encoder substitute. The framework is trained with IU X-Ray dataset for 30 epochs, with Adam optimizer, a learning rate of 0.01 with 0.8 decay rate, binary cross entropy loss for the medical tags, and cross-entropy loss for the generated medical captions. During the framework training process with each image encoder, the parameter that achieves the highest CIDEr score on the validation set is considered the best image encoder parameter and will be used on the test set. On the test set, EfficientNetB3 as an ASGK image encoder has been shown to increase the CIDEr score to 0.35, a significant increase from the 0.28 CIDEr score obtained by the ASGK using DenseNet-121. This score is only a 1% decrease from the best validation score. It suggests that not only EfficientNetB3 increases the framework's performance, it is also less prone to overfitting. This study has demonstrated that EfficientNetB3 is a potential image encoder substitute for DenseNet-121 in the ASGK framework. © 2024 The Authors.

关键词： Medical imaging

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Evaluating the Effectiveness of Transformer Models for Molecular Property Prediction: A Review 9

Evaluating the Effectiveness of Transformer Models for Molec...

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9th International Conference on Information Technology and Digital Applications, ICITDA 2024

作者： Imani, Alyssa Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Binus Graduate Program Bina Nusantara University Computer Science Departement Jakarta11480 Indonesia

ISBN: (纸本)9798331510732

Transformer models, originally successful in natural language processing, are now being applied to chemical and biological studies, excelling in areas such as molecular property prediction, material science, and drug discovery. BERT, a Transformer-based model, has become foundational in cheminformatics, particularly for QSAR (Quantitative Structure-Activity Relationship) modeling and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) evaluations in drug discovery. However, achieving higher accuracy often requires designing more complex models, which can compromise their interpretability. This posing a challenge for researchers who need to understand the reasoning behind the predictions. The trade-off between accuracy and interpretability presents a critical challenge in applying black box models to real-world problems in cheminformatics. This work compares Transformer-based models with traditional machine learning and deep learning approaches, focusing on both interpretability and performance. The goal is to highlight the strengths and limitations of each method, offering insights into their optimal use in drug discovery and material science. © 2024 IEEE.

关键词： Prediction models

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Semi-automated meningioma segmentation with bounding boxes 9th

Semi-automated meningioma segmentation with bounding boxes

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9th International Conference on Computer Science and Computational Intelligence, ICCSCI 2024

作者： Heryanto, Nur Adhianti Isnan, Mahmud Henry, Matthew Martianus Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

Segmentation is manually performed by physicians, which takes considerable time and may be subject to observers. Automating this task can increase efficiency and consistency. Existing studies on meningioma segmentation used data from limited study centers, indicating the need for research on multi-center data to assess generalizability. In this work, two semi-automated methods with bounding box priors, LiteMedSAM and BBU-Net, are evaluated on the brain tumor segmentation (BraTS) 2023 meningioma dataset collected from five study-centers. Preprocessing included exclusion of small tumors, z-score normalization, and extraction of slices that contain tumors, generating 25,602 2D axial magnetic resonance imaging (MRI) scans. A fine-tuning strategy is adopted for LiteMedSAM while BBU-Net is trained from scratch. The models are evaluated using a five-fold cross-validation, with data split at the case level. Results show that while U-Net models can achieve performance close to LiteMedSAM, the foundation model has overall better performance, with more than 90% in all evaluation scores. © 2024 The Authors.

关键词： Magnetic resonance imaging

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LDA Topic Modeling for bioinformatics Terms in arXiv Documents 9th

LDA Topic Modeling for Bioinformatics Terms in arXiv Documen...

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9th International Conference on Computer Science and Computational Intelligence, ICCSCI 2024

作者： Karnyoto, Andrea Stevens Henry, Matthew Martianus Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

A wide variety of disciplines contribute to bioinformatics research, including computer science, biology, chemistry, mathematics, and physics. This study determines the number of research articles published on arXiv classified as bioinformatics topics and the most frequently used bioinformatics terms using topic modeling, Latent Dirichlet Allocation (LDA). An algorithm based on LDA is used to discover topics hidden within large collections of documents through the use of statistical analysis. Our research examined 226453 articles on arXiv between January 2023 and January 2024. As a result, there are more than 10521 articles categorized into bioinformatics topics. Most commonly, 6352 documents are in the "Mathematical Physics" category. The second most popular category is "Computer Science," with 2950 documents. Accordingly, the terms 'RNA,' 'sequence,' 'tree,' and 'homology' are the three most commonly used terms in bioinformatics. The study of RNA plays a vital role in molecular biology;thus, the study of RNA is prevalent in bioinformatics. Sequential data refer to the order in which nucleotides or amino acids can be found in a DNA molecule or a protein. © 2024 The Authors.

关键词： arXiv bioinformatics Latent Dirichlet Allocation

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Dissecting Maize Productivity:Ideotypes Associated with Grain Yield under Drought Stress and Well-watered Conditions

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Journal of Integrative Plant Biology 2012年第12期54卷 1007-1020页

作者： Jill E.Cairns Ciro Sanchez Mateo Vargas Raziel Ordoez Jose Luis Araus Global Maize Program International Maize and Wheat Improvement Center(CIMMYT)Mexico D.F.Mexico Bioinformatics and Statistics Unit International Maize and Wheat Improvement Center(CIMMYT)Mexico D.F.Mexico Unit of Plant Physiology Department of Plant BiologyUniversity of BarcelonaBarcelonaSpain

To increase maize （Zea mays L.） yields in drought-prone environments and offset predicted maize yield losses under future climates, the development of improved breeding pipelines using a multi-disciplinary approach is essential. Elucidating key growth processes will provide opportunities to improve drought breeding progress through the identification of key phenotypic traits, ideotypes, and donors. In this study, we tested a large set of tropical and subtropical maize inbreds and single cross hybrids under reproductive stage drought stress and well-watered conditions. Patterns of biomass production, senescence, and plant water status were measured throughout the crop cycle. Under drought stress, early biomass production prior to anthesis was important for inbred yield, while delayed senescence was important for hybrid yield. Under well-watered conditions, the ability to maintain a high biomass throughout the growing cycle was crucial for inbred yield, while a stay-green pattern was important for hybrid yield. While new quantitative phenotyping tools such as spectral reflectance （Normalized Difference Vegetation Index, NDVI） allowed for the characterization of growth and senescence patterns as well as yield, qualitative measurements of canopy senescence were also found to be associated with grain yield.

关键词： Climate change drought stress ideotypes maize senescence spectral reflectance.

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Impact of DNA-binding position variants on yeast gene expression

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Nucleic Acids Research 2009年第21期37卷 6991-7001页

作者： Swamy, Krishna B.S. Cho, Chung-Yi Chiang, Sufeng Tsai, Zing Tsung-Yeh Tsai, Huai-Kuang Institute of Information Science National Yang-Ming University Taiwan Bioinformatics Program Taiwan International Graduate Program National Yang-Ming University Taiwan Institute of Biomedical Informatics National Yang-Ming University Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei 115 Taiwan

Transcription factors (TFs) regulate gene expression by binding to specific binding sites (TFBSs) in gene promoters. TFBS motifs may contain one or more variable positions. Although the prevailing assumption is that nucleotide variants at such positions are functionally equivalent, there is increasing evidence that such variants play a role in regulation of gene expression. In this article, we propose a method for studying the relationship between the expression of target genes and nucleotide variants in TFBS motifs at a genome-wide scale in Saccharomyces cerevisiae, especially the combinatorial effects of variants at two positions. Our analysis shows that nucleotide variations in more than one-third of variable positions and in 20% of dependent position pairs are highly correlated to gene expression. We define such positions as 'functional'. However, some positions are only functional as dependent pairs, but not individually. In addition, a significant proportion of the functional positions have been well conserved across all yeast-related species studied. We also find that some positions require the presence of co-occurring TFs, while others maintain their functionality in the absence of a co-occurring TF. Our analysis supports the importance of nucleotide variants at variable positions of TFBSs in gene regulation. © The Author(s) 2009. Published by Oxford University Press.

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The bourque distances for mutation trees of cancers 20

The bourque distances for mutation trees of cancers

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20th International Workshop on Algorithms in bioinformatics, WABI 2020

作者： Jahn, Katharina Beerenwinkel, Niko Zhang, Louxin Department of Biosystems Science and Engineering ETH Zurich Basel Switzerland SIB Swiss Institute of Bioinformatics Basel Switzerland Department of Mathematics and Computational Biology Program National University of Singapore Singapore

ISBN: (纸本)9783959771610

Mutation trees are rooted trees of arbitrary node degree in which each node is labeled with a mutation set. These trees, also referred to as clonal trees, are used in computational oncology to represent the mutational history of tumours. Classical tree metrics such as the popular RobinsonFoulds distance are of limited use for the comparison of mutation trees. One reason is that mutation trees inferred with different methods or for different patients often contain different sets of mutation labels. Here, we generalize the RobinsonFoulds distance into a set of distance metrics called Bourque distances for comparing mutation trees. A connection between the RobinsonFoulds distance and the nearest neighbor interchange distance is also presented. © Katharina Jahn, Niko Beerenwinkel, and Louxin Zhang;licensed under Creative Commons License CC-BY

关键词： Bourque distance Clonal trees Mutation trees Phylogenetic trees Robinson–Foulds distance Tree distance Tree metric

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Investigating the genomic basis of metabolic robustness through in silico flux analysis

Investigating the genomic basis of metabolic robustness thro...

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IEEE Conference on Decision and Control

作者： Marcin Imielinski Niels Klitgord Calin Belta N. Klitgord C. Belta University of Pennsylvania School of Medicine Philadelphia PA USA Boston University Graduate Program in Bioinformatics Boston MA USA Boston University Graduate Program in Bioinformatics MA 02115 USA

ISBN: (纸本)9781424431236

We employ a novel implementation of flux balance analysis to investigate the role of genome structure in the maintenance of metabolic robustness. We propose the hypothesis that the genomic organization of a bacterium buffers its metabolome against random gene deletion. To test this hypothesis, we use a novel implementation of producibility analysis to determine the metabolomic impact of gene deletions in the E. coli iJR904 genome-scale metabolic model. From these results, we determine metabolomic fragility, which we compute as the average number of metabolites knocked out across all gene deletions of a given size in a given nutrient media. We apply this analysis for three deletion window sizes (4000, 8000, 16000 bp) across the length of the E. coli genome. We compare these results to those obtained from several null distributions of permuted genomes to assess the impact of E. coli genome organization on its metabolic robustness. Our results strongly suggest that the arrangement of genes on the E. coli genome buffers metabolite producibility against random gene deletion. Our results have interesting implications for the understanding of metabolic network evolution. Future work includes examining our hypothesis for a wider range of deletion sizes and nutrient environments and extending our results to the metabolic networks of other species.

关键词： Genomics bioinformatics Robustness Biochemistry Metabolomics Biological system modeling Organisms Robust control Testing Biological systems

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