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Insect Science 2016年第3期23卷 332-334页

作者： Bin Chen Xian-Hui Wang Zhijian Tu Yong-Ping Huang Institute of Entomology and Molecular Biology Chongqing Normal University Chongqing China State Key Laboratory of IntegratedManagement of Pest Insects & Rodents Institute of Zoology Chinese Academy of Sciences Beijing China Department of Biochemistry Fralin Life Science Institute and Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg Virginia USAand Key Laboratory of Insect Development and Evolutionary Biology Institute of Plant Physiology and Ecology Shanghai Institutes forBiological Sciences Chinese Academy of Sciences Shanghal China

Insects comprise the largest animal group in the world. More than a million insect species have been identified, leaving possibly two to three times more to be discovered. Systematic understanding of the genetic content of an insect species began more than 15 years ago when the genome sequence of the fruit fly, Drosophila melanogaster was reported （Adams et al., 2000）. For the first time, scientists were able to glean unprecedented insights into the genetic blueprint of a model insect, presenting its 13 600 protein coding genes. Such fundamental information opened a floodgate for comparative and functional analysis of these genes and enabled systems approaches to comparative, evolutionary and population genomic studies. In recent years, next-generation and third-generation sequencing platforms brought genome sequencing to more than a hundred insect species, reach- ing far beyond the few well-studied model organisms. The international consortium for insect genomes is work- ing toward an ambitious goal to sequence 5000 species of insects.

关键词： Drosophila melanogaster Insect genetics DNA sequencing Genetic code Insect evolution Insect population genetics

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Knowledge-based versus experimentally acquired distance and angle constraints for NMR structure refinement

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Journal of bioinformatics and computational biology 2008年第2期6卷 283-300页

作者： Cui, Feng Jernigan, Robert Wu, Zhijun Laboratory of Cell Biology National Cancer Institute National Institutes of Health Bethesda MD 20892 United States Program on Bioinformatics and Computational Biology Iowa State University Ames IA 50011 United States Department of Biochemistry Biophysics and Molecular Biology Iowa State University Ames IA 50011 United States Department of Mathematics Iowa State University Ames IA 50011 United States

Nuclear Overhauser effects (NOE) distance constraints and torsion angle constraints are major conformational constraints for nuclear magnetic resonance (NMR) structure refinement. In particular, the number of NOE constraints has been considered as an important determinant for the quality of NMR structures. Of course, the availability of torsion angle constraints is also critical for the formation of correct local conformations. In our recent work, we have shown how a set of knowledge-based short-range distance constraints can also be utilized for NMR structure refinement, as a complementary set of conformational constraints to the NOE and torsion angle constraints. In this paper, we show the results from a series of structure refinement experiments by using different types of conformational constraints - NOE, torsion angle, or knowledge-based constraints - or their combinations, and make a quantitative assessment on how the experimentally acquired constraints contribute to the quality of structural models and whether or not they can be combined with or substituted by the knowledge-based constraints. We have carried out the experiments on a small set of NMR structures. Our preliminary calculations have revealed that the torsion angle constraints contribute substantially to the quality of the structures, but require to be combined with the NOE constraints to be fully effective. The knowledge-based constraints can be functionally as crucial as the torsion angle constraints, although they are statistical constraints after all and are not meant to be able to replace the latter. © 2008 Imperial College Press.

关键词： Knowledge-based distance constraints NMR structure refinement NOE distance constraints Precision and accuracy of NMR structures Torsion angle constraints

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The role of heritability in mapping expression quantitative trait loci

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BMC proceedings 2007年第1-Sup期1 Suppl 1卷 S86页

作者： Song Huang David Ballard Hongyu Zhao Program of Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA. song.huang@yale.edu

Gene expression, as a heritable complex trait, has recently been used in many genome-wide linkage studies. The estimated overall heritability of each trait may be considered as evidence of a genetic contribution to the total phenotypic variation, which implies the possibility of mapping genome regions responsible for the gene expression variation via linkage analysis. However, heritability has been found to be an inconsistent predictor of significant linkage signals. To investigate this issue in human studies, we performed genome-wide linkage analysis on the 3554 gene expression traits of 194 Centre d'Etude du Polymorphisme Humain individuals provided by Genetic Analysis Workshop 15. Out of the 422 expression traits with significant linkage signals identified (LOD > 5.3), 89 traits have low estimated heritability (h2 < 10%), among which 23 traits have an estimated heritability equal to 0. The linkage analysis on individual pedigree shows that the overall LOD scores may result from a few pedigrees with strong linkage signals. Screening gene expressions before linkage analysis using a relatively low heritability (h2 < 20%) may result in a loss of significant linkage signals, especially for trans-acting expression quantitative trait loci (49%).

关键词： Linkage Analysis Heritability Estimate Expression Trait Genetic Analysis Workshop Select Gene Expression

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Prediction of mitochondrial proteins of malaria parasite using improved hybrid method and reduced amino acid alphabet

Prediction of mitochondrial proteins of malaria parasite usi...

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2011 4th International Conference on Biomedical Engineering and Informatics, BMEI 2011

作者： Chen, Ying-Li Li, Qian-Zhong Zhang, Li-Qing Laboratory of Theoretical Biophysics School of Physical Science and Technology Inner Mongolia University Hohhot China Department of Computer Science Virginia Tech Blacksburg VA United States Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg VA United States

ISBN: (纸本)9781424493524

The rate of human death and morbidity due to malaria is increasing in many parts of the developing countries. Thus, there is a great need to understand the critical pathways in malaria parasite in order to develop effective drugs and vaccines. In this work, based on the measure of diversity definition, we introduce the increment of diversity fusion (IDF), an improved hybrid method to predict mitochondrial proteins of malaria parasite. We conduct our experiment on an expanded protein dataset where we require the pairwise identity between two proteins is less than 25%. By choosing amino acids composition as the only input vector, we are able to achieve 65.4% accuracy with 0.32 Mathew's correlation coefficient (MCC) for the jackknife test. Further, incorporting the compositions of the N-terminal and C-terminal regions into the input vector, we show that the prediction results are improved to 82.0% accuracy with 0.64 MCC in the jackknife test. In addition, by combining with the several reduced amino acid alphabet and the hydropathy distribution along protein sequence, we achieve maximum 83.4% accuracy with 0.67 MCC in the jackknife test by using the 64 dipeptide compositions of the reduced amino acid alphabet obtained from Protein Blocks method. © 2011 IEEE.

关键词： Proteins

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Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

JMIR Aging

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JMIR Aging 2025年 8卷 e69504页

作者： Socrates, Vimig Wright, Donald S. Huang, Thomas Fereydooni, Soraya Dien, Christine Chi, Ling Albano, Jesse Patterson, Brian Kanaparthy, Naga Sasidhar Wright, Catherine X. Loza, Andrew Chartash, David Iscoe, Mark Taylor, Richard Andrew Department of Biomedical Informatics and Data Science School of Medicine Yale University New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States Department of Emergency Medicine School of Medicine Yale University New Haven CT United States VA Connecticut Healthcare System US Department of Veterans Affairs West Haven CT United States Department of Pharmacy Yale New Haven Hospital New Haven CT United States BerbeeWalsh Department of Emergency Medicine University of Wisconsin–Madison Madison WI United States Section of Cardiovascular Medicine Department of Internal Medicine Yale School of Medicine New Haven CT United States School of Medicine University College Dublin Dublin Ireland Department of Biostatistics School of Public Health Yale University New Haven CT United States

Background: Polypharmacy, the concurrent use of multiple medications, is prevalent among older adults and associated with increased risks for adverse drug events including falls. Deprescribing, the systematic process of discontinuing potentially inappropriate medications, aims to mitigate these risks. However, the practical application of deprescribing criteria in emergency settings remains limited due to time constraints and criteria complexity. Objective: This study aims to evaluate the performance of a large language model (LLM)–based pipeline in identifying deprescribing opportunities for older emergency department (ED) patients with polypharmacy, using 3 different sets of criteria: Beers, Screening Tool of Older People’s Prescriptions, and Geriatric Emergency Medication Safety Recommendations. The study further evaluates LLM confidence calibration and its ability to improve recommendation performance. Methods: We conducted a retrospective cohort study of older adults presenting to an ED in a large academic medical center in the Northeast United States from January 2022 to March 2022. A random sample of 100 patients (712 total oral medications) was selected for detailed analysis. The LLM pipeline consisted of two steps: (1) filtering high-yield deprescribing criteria based on patients’ medication lists, and (2) applying these criteria using both structured and unstructured patient data to recommend deprescribing. Model performance was assessed by comparing model recommendations to those of trained medical students, with discrepancies adjudicated by board-certified ED physicians. Selective prediction, a method that allows a model to abstain from low-confidence predictions to improve overall reliability, was applied to assess the model’s confidence and decision-making thresholds. Results: The LLM was significantly more effective in identifying deprescribing criteria (positive predictive value: 0.83;negative predictive value: 0.93;McNemar test for paired proportion

关键词： calibration deprescribing emergency medicine geriatrics large language models natural language processing potentially inappropriate medication list

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Doubly-stochastic normalization of the Gaussian kernel is robust to heteroskedastic noise

arXiv

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arXiv 2020年

作者： Landa, Boris Coifman, Ronald R. Kluger, Yuval Program in Applied Mathematics Yale University Interdepartmental Program in Computational Biology and Bioinformatics Yale University Department of Pathology Yale University School of Medicine

A fundamental step in many data-analysis techniques is the construction of an affinity matrix describing similarities between data points. When the data points reside in Euclidean space, a widespread approach is to from an affinity matrix by the Gaussian kernel with pairwise distances, and to follow with a certain normalization (e.g. the row-stochastic normalization or its symmetric variant). We demonstrate that the doubly-stochastic normalization of the Gaussian kernel with zero main diagonal (i.e. no self loops) is robust to heteroskedastic noise. That is, the doubly-stochastic normalization is advantageous in that it automatically accounts for observations with different noise variances. Specifically, we prove that in a suitable high-dimensional setting where heteroskedastic noise does not concentrate too much in any particular direction in space, the resulting (doubly-stochastic) noisy affinity matrix converges to its clean counterpart with rate m−1/2, where m is the ambient dimension. We demonstrate this result numerically, and show that in contrast, the popular row-stochastic and symmetric normalizations behave unfavourably under heteroskedastic noise. Furthermore, we provide a prototypical example of simulated single-cell RNA sequence data with strong intrinsic heteroskedasticity, where the advantage of the doubly-stochastic normalization for exploratory analysis is evident. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic systems

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Construction and Characterization of a Novel Recombinant Attenuated and Replication-Deficient Candidate Human Adenovirus Type 3 Vaccine:"Adenovirus Vaccine Within an Adenovirus Vector"

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Virologica Sinica 2021年第3期36卷 354-364页

作者： Yuqian Yan Shuping Jing Liqiang Feng Jing Zhang Zhiwei Zeng Min Li Shan Zhao Junxian Ou Wendong Lan Wenyi Guan Xiaowei Wu Jianguo Wu Donald Seto Qiwei Zhang Guangdong Provincial Key Laboratory of Tropical Disease Research School of Public HealthSouthern Medical UniversityGuangzhou 510515China Microbiological Laboratory Zhuhai Center for Disease Control and PreventionZhuhai 519000China Guangzhou Institutes of Biomedicine and Health Chinese Academy of SciencesGuangzhou 510530China Guangdong Provincial Key Laboratory of Virology Institute of Medical MicrobiologyJinan UniversityGuangzhou 510632China Bioinformatics and Computational Biology Program School of Systems BiologyGeorge Mason UniversityManassasVA 20110USA

Human adenoviruses(HAd Vs)are highly contagious and result in large number of acute respiratory disease(ARD)cases with severe morbidity and *** adenovirus type 3(HAd V-3)is the most common type that causes ARD outbreaks in Asia,Europe,and the ***,there is currently no vaccine approved for its general *** hexon protein contains the main neutralizing epitopes,provoking strong and lasting *** this study,a novel recombinant and attenuated adenovirus vaccine candidate against HAd V-3 was constructed based on a commercially-available replication-defective HAd V-5 gene therapy and vaccine *** entire HAd V-3 hexon gene was integrated into the E1 region of the vector by homologous recombination using a bacterial *** resultant recombinants expressing the HAd V-3 hexon protein were rescued in AD293 cells,identified and characterized by RT-PCR,Western blots,indirect immunofluorescence,and electron *** potential vaccine candidate had a similar replicative efficacy as the wild-type HAd V-3 ***,and importantly,the vaccine strain had been rendered replication-defective and was incapable of replication in A549 cells after more than twentygeneration passages in AD293 *** represents a significant safety *** mice immunized both intranasally and intramuscularly by this vaccine candidate raised significant neutralizing antibodies against HAd ***,this recombinant,attenuated,and safe adenovirus vaccine is a promising HAd V-3 vaccine *** strategy of using a clinically approved and replication-defective HAd V-5 vector provides a novel approach to develop universal adenovirus vaccine candidates against all the other types of adenoviruses causing ARDs and perhaps other adenovirus-associated diseases.

关键词： Adenovirus vaccine Human adenovirus type 3(HAdV-3) Replication-deficient adenovirus vector Immunity in BALB/c mice Recombination

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Developmental systems biology flourishing on new technologies

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Journal of Genetics and Genomics 2008年第10期35卷 577-584页

作者： Jing-Dong J. Han Yi Liu Huiling Xue Kai Xia Hong Yu Shanshan Zhu Zhang Chen Wei Zhang Zheng Huang Chunyu Jin Bo Xian Jing Li Lei Hou Yixing Han Chaoqun Niu Timothy C. Alcon Chinese Academy of Sciences Key Laboratory of Molecular Developmental Biology Center for Molecular Systems Biology Institute of Genetics and Developmental Biology Chinese Academy of Sciences Beijing 100101 China Key Laboratory of Machine Perception （Ministry of Education） Peking University Beijing 100871 China Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA 50011-1040 USA

Organism development is a systems level process. It has benefited greatly from the recent technological advances in the field of systems biology. DNA microarray, phenome, interactome and transcriptome mapping, the new generation of deep sequencing technologies, and faster and better computational and modeling approaches have opened new frontiers for both systems biologists and developmental biologists to reexamine the old developmental biology questions, such as pattern formation, and to tackle new problems, such as stem cell reprogramming. As showcased in the International Developmental Systems biology Symposium organized by Chinese Academy of Sciences, developmental systems biology is flourishing in many perspectives, from the evolution of developmental systems, to the underlying genetic and molecular pathways and networks, to the genomic, epigenomic and noncoding levels, to the computational analysis and modeling. We believe that the field will continue to reap rewards into the future with these new approaches.

关键词： developmental systems biology new technologies symposium

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Higher-Order Generalization Bounds: Learning Deep Probabilistic programs via PAC-Bayes Objectives

arXiv

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arXiv 2022年

作者： Warrell, Jonathan Gerstein, Mark Program in Computational Biology and Bioinformatics Department of Molecular Biophysics and Biochemistry Yale University New HavenCT06520 United States

Deep Probabilistic programming (DPP) allows powerful models based on recursive computation to be learned using efficient deep-learning optimization techniques. Additionally, DPP offers a unified perspective, where inference and learning algorithms are treated on a par with models as stochastic programs. Here, we offer a framework for representing and learning flexible PAC-Bayes bounds as stochastic programs using DPP-based methods. In particular, we show that DPP techniques may be leveraged to derive generalization bounds that draw on the compositionality of DPP representations. In turn, the bounds we introduce offer principled training objectives for higher-order probabilistic programs. We offer a definition of a higher-order generalization bound, which naturally encompasses single- and multi-task generalization perspectives (including transfer- and meta-learning) and a novel class of bound based on a learned measure of model complexity. Further, we show how modified forms of all higher-order bounds can be efficiently optimized as objectives for DPP training, using variational techniques. We test our framework using single- and multi-task generalization settings on synthetic and biological data, showing improved performance and generalization prediction using flexible DPP model representations and learned complexity measures. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

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High torsional energy disulfides: Relationship between cross-strand disulfides and right-handed staples

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Journal of bioinformatics and computational biology 2006年第1期4卷 155-168页

作者： Haworth, Naomi L. Feng, Lina L. Wouters, Merridee A. Computational Biology and Bioinformatics Program Victor Chang Cardiac Research Institute Darlinghurst NSW 2010 384 Victoria Rd. Australia School of Chemistry University of Sydney Sydney NSW 2006 Australia School of Biotechnology and Biomolecular Sciences University of New South Wales Sydney Sydney NSW 2052 Australia

Redox-active disulfides are capable of being oxidized and reduced under physiological conditions. The enzymatic role of redox-active disulfides in thiol-disulfide reductases is well-known, but redox-active disulfides are also present in non-enzymatic protein structures where they may act as switches of protein function. Here, we examine disulfides linking adjacent β-strands (cross-strand disulfides), which have been reported to be redox-active. Our previous work has established that these cross-strand disulfides have high torsional energies, a quantity likely to be related to the ease with which the disulfide is reduced. We examine the relationship between conformations of disulfides and their location in protein secondary structures. By identifying the overlap between cross-strand disulfides and various conformations, we wish to address whether the high torsional energy of a cross-strand disulfide is sufficient to confer redox activity or whether other factors, such as the presence of the cross-strand disulfide in a strained β-sheet, are required. © Imperial College Press.

关键词： Cross-strand disulfide Disulfide Redox signaling Right-handed staple

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