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arXiv 2025年

作者： Neeley, Matthew B. Qi, Guantong Wang, Guanchu Tang, Ruixiang Mao, Dongxue Liu, Chaozhong Pasupuleti, Sasidhar Yuan, Bo Xia, Fan Liu, Pengfei Liu, Zhandong Hu, Xia Jan and Dan Duncan Neurological Research Institute Texas Children’s Hospital Houston United States Graduate School of Biomedical Sciences Program in Quantitative and Computational Biosciences Baylor College of Medicine Houston United States Graduate School of Biomedical Sciences Program in Genetics and Genomics Baylor College of Medicine Houston United States Department of Computer Science Rice University Houston United States Department of Computer Science Rutgers University NJ United States Department of Pediatrics Baylor College of Medicine Houston United States Department of Molecular and Human Genetics Baylor College of Medicine Houston United States Human Genome Sequencing Center Baylor College of Medicine Houston United States Baylor Genetics Houston United States

Background Rare diseases can be difficult to diagnose due to limited patient data and broad genetic diversity. Despite the advances in variant prioritization tools, many rare disease cases remain undiagnosed. While large language models (LLMs) have performed well in medical exams, their accuracy in diagnosing rare genetic diseases has not yet been evaluated. Methods To identify causal genes for genetic diseases, we benchmarked various LLMs for gene prioritization. We employed multi-agent and Human Phenotype Ontology (HPO) classification approaches to identify patient case groups based on phenotypes categorizing them into different levels of solvability. To address LLM limitations in ranking large gene sets, we used a divide-and-conquer strategy to break down the ranking task into smaller subsets. Mini-batching inputs and limiting the number of generated tokens improved efficiency. Results In its vanilla form, GPT-4 consistently outperformed the other LLMs with an accuracy around 30%. Multi-agent and HPO classification approaches aided us in distinguishing between confidently-solved and challenging cases. In addition, we observed bias towards well-studied genes and input order sensitivity which are drawbacks of LLMs in disease-causal gene prioritization. Our divide-and-conquer strategy enhanced accuracy by overcoming positional and gene frequency biases in literature. This framework, based on benchmarking insights and novel techniques, significantly optimizes the overall process when identifying disease-causal genes for genetic diseases when compared to our baseline evaluation, and thereby better enables the development of targeted diagnostic and therapeutic interventions. Conclusions Using HPO classification and our novel multi-agent techniques, and our LLM divide-and-conquer strategy (1) highlighted the importance of accounting for differences in patient case solvability and (2) yielded improved performance in identifying causal genes for rare diseases when compare

关键词： Gene Ontology

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BPS2025 - Biophysical approaches to study viral proteins at the cellular membranes

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Biophysical Journal 2025年第3期124卷 547a-547a页

作者： Elka R. Georgieva Md Majharul Islam Adeyemi Ogunbowale Saman Majeed Lan Dang Peter P. Borbat Olamide Ishola Elaheh Hadadianpour Arvin S. Delkhosh Juan C. Rueda Amador Steven Ludtke Department of Chemistry and Biochemistry Texas Tech University Lubbock TX USA Graduate Program in Quantitative and Computational Biosciences Graduate School of Biomedical Sciences Baylor College of Medicine Houston TX USA Department of Chemistry and Chemical Biology Cornell University Ithaca NY USA Department of Biochemistry and Molecular Pharmacology Baylor College of Medicine Houston TX USA

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

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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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Proximity-induced equilibrium supercurrent and perfect superconducting diode effect due to band asymmetry

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Physical Review B 2023年第9期108卷 094513-094513页

作者： Pavan Hosur Daniel Palacios Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital Houston Texas 77030 USA and Graduate Program of Quantitative and Computational Biosciences Baylor College of Medicine Houston Texas 77030 USA

We theoretically investigate the consequences of proximity-induced conventional superconductivity in metals that break time-reversal and inversion symmetries through their energy dispersion. We discover behaviors impossible in an isolated superconductor such as an equilibrium supercurrent that apparently violates a no-go theorem and, at suitable topological defects, nonconservation of electric charge reminiscent of the chiral anomaly. The equilibrium supercurrent is expected to be trainable by a helical electromagnetic field in the normal state. Remarkably, if the band asymmetry exceeds the critical current of the parent superconductor in appropriate units, we predict a perfect superconducting diode effect with diode coefficient unity. We propose toroidal metals such as UNi4B and metals with directional scalar spin chiral order as potential platforms.

关键词： Proximity effect Superconducting phase transition s-wave Diodes Noncentrosymmetric materials Superconducting devices BCS theory

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In Situ Structure and Assembly of the Bacterial Multidrug Efflux Pump

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Microscopy and Microanalysis 2019年第S2期25卷 1304-1305页

作者： Xiaodong Shi Muyuan Chen James Michael Bell Zhili Yu Steven J. Ludtke Zhao Wang Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor College of Medicine Houston Texas USA. Graduate Program in Quantitative and Computational Biosciences Baylor College of Medicine Houston Texas USA Department of Molecular and Cellular Biology Baylor College of Medicine Houston Texas USA.

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Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and the greater coronavirus family

Research Square

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Research Square 2020年 rs3rs-95030页

作者： Wang, Chen Konecki, Daniel M. Marciano, David C. Govindarajan, Harikumar Williams, Amanda M. Wastuwidyaningtyas, Brigitta Bourquard, Thomas Katsonis, Panagiotis Lichtarge, Olivier Baylor College of Medicine United States Department of Molecular and Human Genetics United States Quantitative and Computational Biosciences Graduate Program United States Cancer and Cell Biology Graduate Program Baylor College of Medicine HoustonTX77030 United States MAbSilico Nouzilly Centre France Computational and Integrative Biomedical Research Center Baylor College of Medicine HoustonTX77030 United States

Since the first recognized case of COVID-19, more than 100 million people have been infected worldwide. Global efforts in drug and vaccine development to fight the disease have yielded vaccines and drug candidates to cure COVID-19. However, the spread of SARS-CoV-2 variants threatens the continued efficacy of these treatments. In order to address this, we interrogate the evolutionary history of the entire SARS-CoV-2 proteome to identify evolutionarily conserved functional sites that can inform the search for treatments with broader coverage across the coronavirus family. Combining this information with the mutations observed in the current COVID-19 outbreak, we systematically and comprehensively define evolutionarily stable sites that may provide useful drug and vaccine targets and which are less likely to be compromised by the emergence of new virus strains. Several experimentally-validated effective drugs interact with these proposed target sites. In addition, the same evolutionary information can prioritize cross reactive antigens that are useful in directing multi-epitope vaccine strategies to illicit broadly neutralizing immune responses to the betacoronavirus family. Although the results are focused on SARS-CoV-2, these approaches stem from evolutionary principles that are agnostic to the organism or infective agent. © 2020, CC BY.

关键词： Coronavirus

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Identification of spatial co-expression patterns and intra-tissue heterogeneity in spatially resolved transcriptomics by region-specific denoising

Research Square

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Research Square 2021年

作者： Wang, Linhua Liu, Zhandong Graduate Program in Quantitative and Computational Biosciences Baylor College of Medicine Houston United States Jan and Dan Duncan Neurological Research Institute Texas Children’s Hospital Houston United States Department of Pediatrics Baylor College of Medicine Houston United States

We are pleased to introduce a first-of-its-kind tool that combines in-silico region detection and missing value estimation for spatially resolved transcriptomics. Spatial transcriptomics by 10X Visium (ST) is a new technology used to dissect gene and cell spatial organization. Analyzing this new type of data has two main challenges: automatically annotating the major tissue regions and excessive zero values of gene expression due to high dropout rates. We developed a computational tool—MIST—that addresses both challenges by automatically identifying tissue regions and estimating missing gene-expression values for each detected region. We validated MIST detected regions across multiple datasets using manual annotation on the histological staining images as references. We also demonstrated that MIST can accurately recover ST’s missing values through hold-out experiments. Furthermore, we showed that MIST could identify intra-tissue heterogeneity and recover spatial gene-gene co-expression signals. We therefore strongly encourage using MIST before downstream ST analysis because it provides unbiased region annotations and enables accurately denoised spatial gene-expression profiles. © 2021, CC BY.

关键词： Gene expression

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Proximity-induced equilibrium supercurrent and perfect superconducting diode effect due to band asymmetry

arXiv

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arXiv 2022年

作者： Hosur, Pavan Palacios, Daniel Department of Physics Texas Center for Superconductivity University of Houston HoustonTX77004 United States Jan and Dan Duncan Neurological Research Institute Texas Children's Hospital HoustonTX77030 United States Graduate Program of Quantitative and Computational Biosciences Baylor College of Medicine HoustonTX77030 United States

We theoretically investigate the consequences of proximity-induced conventional superconductivity in metals that break time-reversal and inversion symmetries through their energy dispersion. We discover behaviors impossible in an isolated superconductor such as an equilibrium supercurrent that apparently violates a no-go theorem and, at suitable topological defects, non-conservation of electric charge reminiscent of the chiral anomaly. The equilibrium supercurrent is expected to be trainable by a helical electromagnetic field in the normal state. Remarkably, if the band asymmetry exceeds the critical current of the parent superconductor in appropriate units, we predict a perfect superconducting diode effect with diode coefficient unity. We propose toroidal metals such as UNi4B and metals with directional scalar spin chiral order as potential platforms. Copyright © 2022, The Authors. All rights reserved.

关键词： Superconducting materials

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A complete data processing workflow for CryoET and subtomogram averaging

arXiv

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arXiv 2019年

作者： Chen, Muyuan Bell, James M. Shi, Xiaodong Sun, Stella Y. Wang, Zhao Ludtke, Steven J. Verna Marrs and McLean Department of Biochemistry and Molecular Biology Baylor College of Medicine HoustonTX United States Quantitative and Computational Biosciences Graduate Program Baylor College of Medicine HoustonTX United States Jiangsu Province Key Laboratory of Anesthesiology and Jiangsu Province Key Laboratory of Anesthesia and Analgesia Application Xuzhou Medical University Xuzhou Jiangsu China Department of Bioengineering Stanford University StanfordCA United States CryoEM Core at Baylor College of Medicine HoustonTX77030 United States

Electron cryotomography (CryoET) is currently the only method capable of visualizing cells in 3D at nanometer resolutions. While modern instruments produce massive amounts of tomography data containing extremely rich structural information, the data processing is very labor intensive and results are often limited by the skills of the personnel rather than the data. We present an integrated workflow that covers the entire tomography data processing pipeline, from automated tilt series alignment to subnanometer resolution subtomogram averaging. This workflow greatly reduces human effort and increases throughput, and is capable of determining protein structures at state-of-the-art resolutions for both purified macromolecules and cells. Copyright © 2019, The Authors. All rights reserved.

关键词： Tomography

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The 3.5-Å CryoEM Structure of Nanodisc-Reconstituted Yeast Vacuolar ATPase V_o Proton Channel

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Molecular Cell 2018年第6期69卷 993-1004.e3页

作者： Roh, Soung-Hun Stam, Nicholas J. Hryc, Corey F. Couoh-Cardel, Sergio Pintilie, Grigore Chiu, Wah Wilkens, Stephan Department of Bioengineering and James H. Clark Center Stanford University Stanford 94305 CA United States Biosciences Division SLAC National Accelerator Laboratory Menlo Park 94025 CA United States Department of Biochemistry and Molecular Biology SUNY Upstate Medical University Syracuse 13210 NY United States Graduate Program in Quantitative and Computational Biosciences Baylor College of Medicine Houston 77030 TX United States Verna and Marrs McLean Department of Biochemistry and Molecular Biology Baylor College of Medicine Houston 77030 TX United States

The molecular mechanism of transmembrane proton translocation in rotary motor ATPases is not fully understood. Here, we report the 3.5-Å resolution cryoEM structure of the lipid nanodisc-reconstituted V_o proton channel of the yeast vacuolar H⁺-ATPase, captured in a physiologically relevant, autoinhibited state. The resulting atomic model provides structural detail for the amino acids that constitute the proton pathway at the interface of the proteolipid ring and subunit a. Based on the structure and previous mutagenesis studies, we propose the chemical basis of transmembrane proton transport. Moreover, we discovered that the C terminus of the assembly factor Voa1 is an integral component of mature V_o. Voa1’s C-terminal transmembrane α helix is bound inside the proteolipid ring, where it contributes to the stability of the complex. Our structure rationalizes possible mechanisms by which mutations in human V_o can result in disease phenotypes and may thus provide new avenues for therapeutic interventions. Here, we report the 3.5-Å resolution cryoEM structure of lipid nanodisc-reconstituted yeast vacuolar H⁺-ATPase V_o proton channel. The resulting atomic model provides insight into the chemical basis of transmembrane proton transport. Moreover, we discovered that the C terminus of the assembly factor Voa1 is an integral component of mature V_o. © 2018 Elsevier Inc.

关键词： cryoEM lipid nanodisc membrane protein structure proton pumping reversible disassembly V-ATPase assembly Vo proton channel vacuolar H+-ATPase Voa1

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