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Convergent Usage of Amino Acids in Human Cancers as A Reversed Process of Tissue Development

Genomics, Proteomics & bioinformatics 2022年第1期20卷 147-162页

作者： Yikai Luo Han Liang Graduate Program in Quantitative and Computational Biosciences Baylor College of MedicineHoustonTX 77030USA Department of Bioinformatics and Computational Biology The University of Texas MD Anderson Cancer CenterHoustonTX 77030USA Department of Systems Biology The University of Texas MD Anderson Cancer CenterHoustonTX 77030USA

Genome-and transcriptome-wide amino acid usage preference across different species is a well-studied phenomenon in molecular evolution,but its characteristics and implication in cancer evolution and therapy remain largely ***,we analyzed large-scale transcriptome/proteome profiles,such as The Cancer Genome Atlas(TCGA),the Genotype-Tissue Expression(GTEx),and the Clinical Proteomic Tumor Analysis Consortium(CPTAC),and found that compared to normal tissues,different cancer types showed a convergent pattern toward using biosynthetically low-cost amino *** a pattern can be accurately captured by a single index based on the average biosynthetic energy cost of amino acids,termed energy cost per amino acid(ECPA).With this index,we further compared the trends of amino acid usage and the contributing genes in cancer and tissue development,and revealed their reversed ***,focusing on the liver,a tissue with a dramatic increase in ECPA during development,we found that ECPA represents a powerful biomarker that could distinguish liver tumors from normal liver samples consistently across 11 independent patient cohorts and outperforms any index based on single *** study reveals an important principle underlying cancer evolution and suggests the global amino acid usage as a system-level biomarker for cancer diagnosis.

关键词： Amino acid usage Tissue development Biosynthetic energy Diagnostic biomarker

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Synthetic Gene Design with a Large Number of Hidden Stop Codons

Synthetic Gene Design with a Large Number of Hidden Stop Cod...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Vinhthuy Phan Sudip Saha Ashutosh Pandey Wong Tit-Yee Department of Computer Science The Bioinformatics Program University of Memphis USA Department of Computer Science University of Memphis USA The Bioinformatics Program University of Memphis USA Department of Biology University of Memphis USA

Hidden stop codons are nucleotide triples TAA, TAG, and TGA that appear in the second and third reading frames of a protein coding gene. Recent studies reported biological evidence suggesting that hidden stop codons are important in preventing misread of mRNA, which is often detrimental to the cell. We study the problem of designing protein-encoding genes with large number of hidden stop codons under biological constraints including GC content and codon usage of individual organism. In simpler models, we obtained provably optimal results. In more complex models, the designed genes have many more hidden stop codons than wild-type genes do, as observed in an experiment with 8 genomes with a wide range of GC content and codon usage.

关键词： Proteins bioinformatics Organisms Amino acids Genetics Technical Activities Guide -TAG Genomics Computer science Biological system modeling Synthetic biology

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Overview of biological database mapping services for interoperation between different 'omics' datasets

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Human Genomics 2011年第6期5卷 703-708页

作者： Chavan, Shweta S. Shaughnessy Jr., John D. Edmondson, Ricky D. University of Arkansas Little Rock (UALR) University of Arkansas Medical Sciences (UAMS) Joint Bioinformatics Program AR 72204 United States Myeloma Institute for Research and Therapy UAMS Little Rock AR 72205 United States

Many primary biological databases are dedicated to providing annotation for a specific type of biological molecule such as a clone, transcript, gene or protein, but often with limited cross-references. Therefore, enhanced mapping is required between these databases to facilitate the correlation of independent experimental datasets. For example, molecular biology experiments conducted on samples (DNA, mRNA or protein) often yield more than one type of 'omics' dataset as an object for analysis (eg a sample can have a genomics as well as proteomics expression dataset available for analysis). Thus, in order to map the two datasets, the identifier type from one dataset is required to be linked to another dataset, so preventing loss of critical information in downstream analysis. This identifier mapping can be performed using identifier converter software relevant to the query and target identifier databases. This review presents the publicly available web-based biological database identifier converters, with comparison of their usage, input and output formats, and the types of available query and target database identifier types. © HENRY STEWART PUBLICATIONS.

关键词： Biological database identifier converter Genomics Identifier mapping Omics Proteomics

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Multiplexed Nanoscopy via Buffer Exchange

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ACS Nano 2024年第34期18卷 23445-23456页

作者： Chang, Ting-Jui Ben Yang, T. Tony Department of Electrical Engineering National Taiwan University Taipei10617 Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei10617 Taiwan Department of Physics National Taiwan University Taipei10617 Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica and National Taiwan University Taipei10617 Taiwan

Understanding cellular functions, particularly in their intricate complexity, can greatly benefit from the spatial mapping of diverse molecules through multitarget single-molecule localization microscopy (SMLM). Existing methodologies, primarily restricting the encoding dimensions to color and lifetime or requiring cyclic staining, often involve broad chromatic detection, specialized optical configurations, or sophisticated labeling techniques. Here, we propose a simple approach called buffer-exchange stochastic optical reconstruction microscopy (beSTORM), which introduces an additional dimension to differentiate between single molecules irrespective of their spectral properties. This method leverages the distinguishable photoblinking responses to distinct buffer conditions, offering a straightforward yet effective means of fluorophore discrimination. Through buffer exchanges, beSTORM achieves multitarget SMLM imaging with minimal crosstalk. Direct integration with expansion microscopy (ExM) demonstrates its capability to resolve up to six proteins at the molecular level within a single emission color without chromatic aberration. Overall, beSTORM presents a highly compatible imaging platform, promising significant advancements in highly multiplexed nanoscopy for exploring multiple targets in biological systems with nanoscale precision. © 2024 The Authors. Published by American Chemical Society.

关键词： Stochastic systems

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Local dimension-reduced dynamical spatio-temporal models for resting state network estimation

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Brain Informatics 2015年第2期2卷 53-63页

作者： Vieira, Gilson Amaro, Edson Baccalá, Luiz A. Inter-institutional Grad Program on Bioinformatics University of São Paulo São Paulo Brazil LIM-44 Department of Radiology University of São Paulo São Paulo Brazil Escola Politécnica University of São Paulo São Paulo Brazil

To overcome the limitations of independent component analysis (ICA), today’s most popular analysis tool for investigating whole-brain spatial activation in resting state functional magnetic resonance imaging (fMRI), we present a new class of local dimension-reduced dynamical spatio-temporal model which dispenses the independence assumptions that severely limit deeper connectivity descriptions between spatial components. The new method combines novel concepts of group sparsity with contiguity-constrained clusterization to produce physiologically consistent regions of interest in illustrative fMRI data whose causal interactions may then be easily estimated, something impossible under the usual ICA assumptions. © 2015, The Author(s).

关键词： Activation analysis

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Segment Self-Repulsion is the Major Driving Force of Influenza Genome Packaging

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Physical Review Letters 2013年第9期110卷 098104-098104页

作者： Sergey V. Venev Konstantin B. Zeldovich Program in Bioinformatics and Integrative Biology University of Massachusetts Medical School 55 Lake Avenue North Worcester Massachusetts 01655 USA

The genome of influenza A virus consists of eight separate RNA segments, which are selectively packaged into virions prior to virus budding. The microscopic mechanism of highly selective packaging involves molecular interactions between packaging signals in the genome segments and remains poorly understood. We propose that the condition of proper packaging can be formulated as a large gap between RNA-RNA interaction energies in the viable virion with eight unique segments and in improperly packed assemblages lacking the complete genome. We then demonstrate that selective packaging of eight unique segments into an infective influenza virion can be achieved by self-repulsion of identical segments at the virion assembly stage, rather than by previously hypothesized intricate molecular recognition of particular segments. Using Monte Carlo simulations to maximize the energy gap, without any other assumptions, we generated model eight-segment virions, which all display specific packaging, strong self-repulsion of the segments, and reassortment patterns similar to natural influenza. The model provides a biophysical foundation of influenza genome packaging and reassortment and serves as an important step towards robust sequence-driven prediction of reassortment patterns of the influenza virus.

关键词： INFLUENZA A virus GENOMES MOLECULAR interactions RNA-RNA interactions MOLECULAR recognition MONTE Carlo method

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ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION FIGURES

ENERGY-BASED ARCHITECTURE FOR CLASSIFICATION OF PUBLICATION ...

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Annual ORNL Biomedical Sciences and Engineering Conference on Collaborative Biomedical Innovations

作者： P. E. Barbano M. L. Nagy M. Krauthammer Department of Mathematics Yale University Program for Computational Biology and Bioinformatics Yale University

ISBN: (纸本)9781479921195

We present an implementation of the experimental and theoretical results obtained in the analysis of text and image content of biomedical publications. Particularly, we propose a novel optical recognition system using an adaptive algorithm for the classification and analysis of highly heterogeneous images in research papers. When compared with conventional algorithms, our technology substantially increases the probability of detection and classification of images buried in text or obscured by other images. We report successful testing of the new architecture using PubMed publications.

关键词： publications images ARCHITECTURE Classification of algorithms new buildings Taxonomy texts optical identification WWOX gene Image classification

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A block-based evolutionary optimization strategy to investigate gene-gene interactions in genetic association studies

A block-based evolutionary optimization strategy to investig...

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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Joel Fontanarosa Yang Dai Bioinformatics Program Department of Bioengineering University of Illinois Chicago Chicago IL USA

Multi-locus interactions in genetic association studies are believed to influence the heritability of a number of common diseases. In this study, we propose a discrete optimization strategy to improve the power and computational efficiency of multi-locus association analysis. We implemented an adaptive evolutionary algorithm in combination with a linkage disequilibrium-based discretization approach to reduce the need for exhaustive search for combinations by taking advantage of inherent genomic structure. The method was applied to several simulated disease models as well as to a real genome-wide association study. The results indicate that our method performs as well as or better than the most powerful competing methods for detecting true interactions, and it achieves this performance with improved computational efficiency.

关键词： bioinformatics Genomics Computational modeling Couplings Diseases Data models

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Integrating immunoinformatics and computational epitope prediction for a vaccine candidate against respiratory syncytial virus

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Infectious Disease Modelling 2024年第3期9卷 763-774页

作者： Truc Ly Nguyen Heebal Kim Department of Agricultural Biotechnology and Research Institute of Agriculture and Life Sciences Seoul National UniversitySeoul08826Republic of Korea Interdisciplinary Program in Bioinformatics Seoul National UniversitySeoul08826Republic of Korea eGnome Inc.Seoul05836Republic of Korea

Respiratory syncytial virus(RSV)poses a significant global health threat,especially affecting infants and the *** this,the present study proposes an innovative approach to vaccine design,utilizing immunoinformatics and computational *** analyzed RSV's structural proteins across both subtypes A and B,identifying potential helper T lymphocyte,cytotoxic T lymphocyte,and linear B lymphocyte *** such as antigenicity,allergenicity,toxicity,and cytokine-inducing potential were rigorously ***,we evaluated the conservancy of these epitopes and their population coverage across various RSV *** comprehensive analysis identified six major histocompatibility complex class I(MHC-I)binding,five MHC-II binding,and three B-cell *** were integrated with suitable linkers and adjuvants to form the ***,molecular docking and molecular dynamics simulations demonstrated stable interactions between the vaccine candidate and human Toll-like receptors(TLR4 and TLR5),with a notable preference for *** simulation analysis underscored the vaccine's potential to elicit a strong immune *** study presents a promising RSV vaccine candidate and offers theoretical support,marking a significant advancement in vaccine development ***,the promising in silico findings need to be further validated through additional in vivo studies.

关键词： Respiratory syncytial virus Multiepitope vaccine Immunoinformatics Docking molecular Molecular dynamics simulation Immune simulation

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The crystal structure of a replicative hexameric helicase DnaC and its complex with single-stranded DNA

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Nucleic Acids Research 2009年第3期37卷 804-814页

作者： Lo, Yu-Hua Tsai, Kuang-Lei Sun, Yuh-Ju Chen, Wei-Ti Huang, Cheng-Yang Hsiao, Chwan-Deng Institute of Molecular Biology Academia Sinica Taipei 115 Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Hsinchu 300 Taiwan Taiwan International Graduate Program Academia Sinica Taipei 115 Taiwan

DNA helicases are motor proteins that play essential roles in DNA replication, repair and recombination. In the replicative hexameric helicase, the fundamental reaction is the unwinding of duplex DNA;however, our understanding of this function remains vague due to insufficient structural information. Here, we report two crystal structures of the DnaB-family replicative helicase from Geobacillus kaustophilus HTA426 (Gk DnaC) in the apo-form and bound to single-stranded DNA (ssDNA). The Gk DnaC-ssDNA complex structure reveals that three symmetrical basic grooves on the interior surface of the hexamer individually encircle ssDNA. The ssDNA-binding pockets in this structure are directed toward the N-terminal domain collar of the hexameric ring, thus orienting the ssDNA toward the DnaG primase to facilitate the synthesis of short RNA primers. These findings provide insight into the mechanism of ssDNA binding and provide a working model to establish a novel mechanism for DNA translocation at the replication fork. © 2008 The Author(s).

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