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MorPhiC Consortium: towards functional characterization of all human genes

Nature 2025年第8050期638卷 351-359页

作者： Adli, Mazhar Przybyla, Laralynne Burdett, Tony Burridge, Paul W. Cacheiro, Pilar Chang, Howard Y. Engreitz, Jesse M. Gilbert, Luke A. Greenleaf, William J. Hsu, Li Huangfu, Danwei Hung, Ling-Hong Kundaje, Anshul Li, Shuzhao Parkinson, Helen Qiu, Xiaojie Robson, Paul Schürer, Stephan C. Shojaie, Ali Skarnes, William C. Smedley, Damian Studer, Lorenz Sun, Wei Vidović, Dušica Vierbuchen, Thomas White, Brian S. Yeung, Ka Yee Yue, Feng Zhou, Ting Žurauskienė, Justina Zhong, Aaron Zheng, Shujian Zhao, Hengqiang Zhang, Nan Zhang, Zhehao Zhang, Stephen Zeng, Tony Yu, Bo Yordanova, Galabina N. Yang, Dapeng Xing, De Wang, Xianming Wang, Ping Torre, Denis Tang, Wenzhuo Shivalikanjli, Anu Sengupta, Kaustav Seker, Fidan Ventura, Enrique Sapena Ross, Nicolette C. Rivera-Diaz, Jamilex Rana, Arushi Pongpamorn, Praeploy Poirion, Olivier B. Pillai, Ajay Pilarczyk, Marcin Parker, Devon Ning, Gang Neyisci, Ozlem Nasam, Niharika Mittal, Varun Mitchell, Joshua M. Metzl-Raz, Eyal Meng, Chen Melo-Carrillo, Adrian McDonough, Justin A. Marengo, Gabriel Mao, Yuzhen Leite, Davi Lyra Luo, Renhe Liu, Nianping Liu, Dingyu Liu, Zukai Liu, Si Li, Zhaoheng Kraft, Katerina Koci, Orges A. Kirsammer, Gina Kendra, Angelina Hutter, Carolyn Huebner, Aaron J. Huang, Yung-Hsin Hu, Nan Gupta, Dipayan Gupta, Revant Guo, Tingfeng Griffiths, Alexandra M. Goyal, Juhee Glenn, Rachel A. Garofalo, Jessica L. Fukuda, Bryce Nobutoshi Fu, Yihao Flynn, William F. Flores, Jesse Fletcher, Colin F. Fleming, Patrick J. Felsenfeld, Adam L. Eraslan, Basak Doty, Anthony Dahlstrom, Thomas J. Chung, Caty E. Choudhary, Anshul Cho, Hyein S. Chen, Xintong Chen, Sijie Chan, Chia Baroch, Jacob J. Baker, Dylan S. Bai, Tao Avireddy, Rohan N. V. S. R. K. Amiri, Anahita Diniz, Juliana Alcoforado Abbaszadeh, Neda Robert H. Lurie Comprehensive Cancer Center Department of Obstetrics and Gynecology Northwestern University Feinberg School of Medicine Chicago IL United States Department of Biochemistry and Biophysics University of California San Francisco CA United States Omics Section European Bioinformatics Institute (EMBL-EBI) European Molecular Biology Laboratory Hinxton United Kingdom Department of Pharmacology Center for Pharmacogenomics Northwestern University Feinberg School of Medicine Evanston IL United States William Harvey Research Institute Clinical Pharmacology and Precision Medicine Queen Mary University of London London United Kingdom Department of Dermatology Stanford University Stanford CA United States Department of Genetics Stanford University Stanford CA United States Basic Science and Engineering (BASE) Initiative Stanford University Stanford CA United States Department of Urology University of California San Francisco CA United States Department of Biostatistics Public Health Sciences Fred Hutchinson Cancer Center Seattle WA United States Developmental Biology Program Sloan Kettering Institute New York NY USA School of Engineering and Technology University of Washington Tacoma Tacoma WA United States Departments of Genetics and Computer Science Stanford University Stanford CA United States Jackson Laboratory for Genomic Medicine Farmington CT United States Knowledge Management Section European Bioinformatics Institute (EMBL-EBI) European Molecular Biology Laboratory Hinxton United Kingdom Molecular and Cellular Pharmacology Sylvester Comprehensive Cancer Center University of Miami Coral Gables FL USA Department of Biostatistics University of Washington Seattle WA United States Department of Biochemistry and Molecular Genetics Robert H. Lurie Comprehensive Cancer Center Northwestern University Feinberg School of Medicine Chicago IL United States

Recent advances in functional genomics and human cellular models have substantially enhanced our understanding of the structure and regulation of the human genome. However, our grasp of the molecular functions of human genes remains incomplete and biased towards specific gene classes. The Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Consortium aims to address this gap by creating a comprehensive catalogue of the molecular and cellular phenotypes associated with null alleles of all human genes using in vitro multicellular systems. In this Perspective, we present the strategic vision of the MorPhiC Consortium and discuss various strategies for generating null alleles, as well as the challenges involved. We describe the cellular models and scalable phenotypic readouts that will be used in the consortium's initial phase, focusing on 1,000 protein-coding genes. The resulting molecular and cellular data will be compiled into a catalogue of null-allele phenotypes. The methodologies developed in this phase will establish best practices for extending these approaches to all human protein-coding genes. The resources generated-including engineered cell lines, plasmids, phenotypic data, genomic information and computational tools-will be made available to the broader research community to facilitate deeper insights into human gene functions. © 2025. Springer Nature Limited.

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PULASki: Learning inter-rater variability using statistical distances to improve probabilistic segmentation

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Medical Image Analysis 2025年 103卷 103623页

作者： Chatterjee, Soumick Gaidzik, Franziska Sciarra, Alessandro Mattern, Hendrik Janiga, Gábor Speck, Oliver Nürnberger, Andreas Pathiraja, Sahani Data and Knowledge Engineering Group Faculty of Computer Science Otto von Guericke University Magdeburg Germany Genomics Research Centre Human Technopole Milan Italy Laboratory of Fluid Dynamics and Technical Flows Otto von Guericke University Magdeburg Germany Department of Biomedical Magnetic Resonance Faculty of Natural Sciences Otto von Guericke University Magdeburg Germany MedDigit Department of Neurology Medical Faculty University Hospital Magdeburg Germany German Centre for Neurodegenerative Disease Magdeburg Germany Centre for Behavioural Brain Sciences Magdeburg Germany School of Mathematics & Statistics UNSW Sydney Australia

In the domain of medical imaging, many supervised learning based methods for segmentation face several challenges such as high variability in annotations from multiple experts, paucity of labelled data and class imbalanced datasets. These issues may result in segmentations that lack the requisite precision for clinical analysis and can be misleadingly overconfident without associated uncertainty quantification. This work proposes the PULASki method as a computationally efficient generative tool for biomedical image segmentation that accurately captures variability in expert annotations, even in small datasets. This approach makes use of an improved loss function based on statistical distances in a conditional variational autoencoder structure (Probabilistic UNet), which improves learning of the conditional decoder compared to the standard cross-entropy particularly in class imbalanced problems. The proposed method was analysed for two structurally different segmentation tasks (intracranial vessel and multiple sclerosis (MS) lesion) and compare our results to four well-established baselines in terms of quantitative metrics and qualitative output. These experiments involve class-imbalanced datasets characterised by challenging features, including suboptimal signal-to-noise ratios and high ambiguity. Empirical results demonstrate the PULASKi method outperforms all baselines at the 5% significance level. Our experiments are also of the first to present a comparative study of the computationally feasible segmentation of complex geometries using 3D patches and the traditional use of 2D slices. The generated segmentations are shown to be much more anatomically plausible than in the 2D case, particularly for the vessel task. Our method can also be applied to a wide range of multi-label segmentation tasks and is useful for downstream tasks such as hemodynamic modelling (computational fluid dynamics and data assimilation), clinical decision making, and treatment planning. © 2

关键词： Image segmentation

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knowledge discovery in multidimensional knowledge representation framework: An integrative approach for the visualization of text analytics results

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Iran Journal of computer science 2018年第4期1卷 199-216页

作者： Zenkert, Johannes Klahold, André Fathi, Madjid Department of Electrical Engineering and Computer Science Institute of Knowledge Management and Knowledge Based Systems University of Siegen Siegen Germany

Visualization of results is one of the central challenges in big data analytics and integrative text mining. With a growing amount of unstructured data and different perspectives on big data, knowledge graphs have difficulties to simultaneously represent and visualize all analyzed dimensions of knowledge. This paper proposes integrative text mining as a solution to combine results from different dimensional analysis in a multidimensional knowledge representation (MKR) for knowledge discovery and visualization purpose. Analysis results from named entity recognition, topic detection, sentiment analysis and the extraction of semantic relationships are, therefore, integrated into a common representation structure. In the implementation part of this research, an application is introduced which utilizes MKR based on the results of stated text mining methods applied on a German and English news data set. State-of-the-art visualizations are used in the application and MKR adaptively transforms the visualization type of the knowledge graph according to the selected context for knowledge discovery. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Information visualization knowledge graphs knowledge representation Natural language processing Text mining

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A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset

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Journal of Donghua University(English Edition) 2006年第6期23卷 1-4,9页

作者：武坤姜保庆魏庆 Institute of Data and Knowledge Engineering Henan University Institute of Data and Knowledge Engineering Henan University The Computer Science Department Henan University of Finance and Economics

The classical algorithm of finding association rules generated by a frequent itemset has to generate all non-empty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient.

关键词： association rule frequent itemset breath-first,depth-first consequent.

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Efficient Communication in Wireless Sensor Networks Using Optimized Energy Efficient Engroove Leach Clustering Protocol

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Tsinghua science and Technology 2024年第4期29卷 985-1001页

作者： N.Meenakshi Sultan Ahmad A.V.Prabu J.Nageswara Rao Nashwan Adnan Othman Hikmat A.M.Abdeljaber R.Sekar Jabeen Nazeer SRM Institute of Science and Technology KattankulathurChennai 603203India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj 11942Saudi Arabia University Center for Research and Development(UCRD) Department of Computer Science and EngineeringChandigarh UniversityGharuanMohali 140413India Department of ECE Koneru Lakshmaiah Education FoundationVaddeswaramGuntur 522502India Department of Computer Science and Engineering Lakireddy Balireddy College of Engineering(A)NTR District 521230India Department of Computer Engineering College of EngineeringKnowledge UniversityErbil 44001Iraq Department of Computer Science Faculty of Information TechnologyApplied Science Private UniversityAmman 11937Jordan Department of Electronics and Communication Engineering(ECE) School of EngineeringPresidency UniversityBangalore 834001India

The Wireless Sensor Network(WSN)is a network that is constructed in regions that are inaccessible to human *** widespread deployment of wireless micro sensors will make it possible to conduct accurate environmental monitoring for a use in both civil and military *** make use of these data to monitor and keep track of the physical data of the surrounding environment in order to ensure the sustainability of the *** data have to be picked up by the sensor,and then sent to the sink node where they may be *** nodes of the WSNs are powered by batteries,therefore they eventually run out of *** energy restriction has an effect on the network life span and environmental *** objective of this study is to further improve the Engroove Leach(EL)protocol’s energy efficiency so that the network can operate for a very long time while consuming the least amount of *** lifespan of WSNs is being extended often using clustering and routing *** Meta Inspired Hawks Fragment Optimization(MIHFO)system,which is based on passive clustering,is used in this study to do *** cluster head is chosen based on the nodes’residual energy,distance to neighbors,distance to base station,node degree,and node *** on distance,residual energy,and node degree,an algorithm known as Heuristic Wing Antfly Optimization(HWAFO)selects the optimum path between the cluster head and Base Station(BS).They examine the number of nodes that are active,their energy consumption,and the number of data packets that the BS *** overall experimentation is carried out under the MATLAB *** the analysis,it has been discovered that the suggested approach yields noticeably superior outcomes in terms of throughput,packet delivery and drop ratio,and average energy consumption.

关键词： wireless sensor networks energy efficient engroove leach protocol meta inspired Hawks fragment optimization heuristic wing antfly optimization

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A fast rigid registration algorithm for medical images

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Journal of Fiber Bioengineering and Informatics 2014年第3期7卷 409-418页

作者： Feng, Yuncong Li, Xiongfei Zhang, Xiaoli Ding, Tienan Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China Department of Computer Science and Technology Changchun China

Image registration is a vital research branch in medical image processing and analysis. In this paper, we proposed a new framework for rigid medical image registration. It can also be regarded as a pre-processing of non-rigid image registration algorithms. The interest of the algorithm lies in its simplicity and high e±ciency. In the registration algorithm, we firstly segmented the reference image and °oat image into two parts: tissue parts and background parts. Then the centers of the two images were located through performing distance transform on the two segmented tissue images. Finally, we detected the longest radius of the two tissue regions, by which we determined the rotating angle. We tested the registration algorithm on dozens of medical images, and the experimental results show us that the algorithm is competent for medical image registration.

关键词： Image registration

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Degradation modeling of degradable copolymers for biomimetic scaffolds

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Friction 2020年第3期8卷 594-603页

作者： Taohong ZHANG Yue GAO Lingling ZHU Qingfeng ZENG Ming ZHOU Computer Department School of Computer&Communication EngineeringUniversity of Science and Technology Beijing(USTB)Beijing 100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing 100083China State Key Laboratory of Tribology School of Mechanical EngineeringTsinghua UniversityBeijing 100084China

Biomimetic scaffolds provide a suitable growth environment for tissue engineering and demonstrate good potential for application in biomedical ***-sized copolymerized biomimetic scaffolds degrade differently,and the degradation rate is affected by the copolymerization *** study of the degradation property is the foundational research necessary for realizing individualized biomimetic scaffold *** degradation performance of polyesters with different copolymerization ratios has been widely reported;however,the modeling of this performance has been rarely *** this research,the degradation of copolymers was studied with multi-scale modeling,in which the copolymers were dispersed in a cellular manner,the chain break time was simulated,and the chain selection was based on the Monte Carlo(MC)*** probability model of the copolymer's chain break position was established as a//roulette,/model,whose probability values were estimated by the calculation of the potential energy difference at different chain break positions by molecular dynamics that determined the position of chain shear,thereby fully realizing the simulation of the chain micro-break *** diffusion of the oligomers was then calculated using the macro diffusion equation,and the degradation process of the copolymer was simulated by three-scale coupling *** calculation results were in good agreement with the experimental data,demonstrating the effectiveness of the proposed method.

关键词： copolymer for biomimetic scaffolds copolymerization ratio degradation modeling multi-scale model probability model for chain break location

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Fine-Grained Cross-Modal Fusion Based Refinement for Text-to-Image Synthesis

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Chinese Journal of Electronics 2023年第6期32卷 1329-1340页

作者： SUN Haoran WANG Yang LIU Haipeng QIAN Biao Department of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of EducationHefei University of Technology

Text-to-image synthesis refers to generating visual-realistic and semantically consistent images from given textual descriptions. Previous approaches generate an initial low-resolution image and then refine it to be high-resolution. Despite the remarkable progress, these methods are limited in fully utilizing the given texts and could generate text-mismatched images, especially when the text description is complex. We propose a novel finegrained text-image fusion based generative adversarial networks(FF-GAN), which consists of two modules: Finegrained text-image fusion block(FF-Block) and global semantic refinement(GSR). The proposed FF-Block integrates an attention block and several convolution layers to effectively fuse the fine-grained word-context features into the corresponding visual features, in which the text information is fully used to refine the initial image with more details. And the GSR is proposed to improve the global semantic consistency between linguistic and visual features during the refinement process. Extensive experiments on CUB-200 and COCO datasets demonstrate the superiority of FF-GAN over other state-of-the-art approaches in generating images with semantic consistency to the given texts.

关键词： Visualization Fuses Convolution Semantics Linguistics Benchmark testing Generative adversarial networks

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BERST: An Engine and Tool for Exploring Biomedical Entities and Relationships

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Chinese Journal of Electronics 2019年第4期28卷 797-804页

作者： BAI Tian GE Yan YANG Changqing LIU Xiaohua GONG Leiguang WANG Ye HUANG Lan College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Yantai Intelligent Information Technologies Ltd. Department of Computer Science and Technology Zhuhai College of Jilin University

To facilitate the search of rapidly growing biomedical knowledge in literature, we developed a Biomedical entity-relationship search tool(BERST). It is also a biomedical knowledge integration framework, which presently contains six popular databases represented in terms of a network of concepts and relations extracted from these knowledge sources. Users search the integrated knowledge network by entering keywords, and BERST returns a sub-network matching and representing the keywords and their relationships. The resulting graph can be navigated interactively allowing users to explore specific paths between any two nodes representing potentially interesting relationships between them. A graphical UI was developed to provide a more intuitive and overall view of the information being searched and studied. BERST framework can be naturally expanded to integrate other biomedical knowledge sources. BERST is implemented as a Java web application.

关键词： Biomedical ontology Relationship mining Relationship searching tool

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Security challenges and defense approaches for blockchain-based services from a full-stack architecture perspective

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Blockchain(Research and Applications) 2023年第3期4卷 18-38页

作者： Hongsong Chen Xietian Luo Lei Shi Yongrui Cao Yongpeng Zhang Department of Computer Science University of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

As an advantageous technique and service,the blockchain has shown great development and application ***,its security has also met great challenges,and many security vulnerabilities and attack issues in blockchain-based services have ***,security issues of blockchain have attracted extensive ***,there is still a lack of blockchain security research from a full-stack architecture perspective,as well as representative quantitative experimental reproduction and *** aim to provide a security architecture to solve security risks in blockchain services from a full-stack architecture ***,we propose a formal definition of the full-stack security architecture for blockchain-based services,and we also propose a formal expression of security issues and defense solutions from a full-stack security *** use ConCert to conduct a smart contract formal verification experiment by property-based *** security vulnerabilities of blockchain services in the Common Vulnerabilities and Exposures(CVE)and China Nation Vulnerability Database(CNVD)are selected and ***,three real contract-layer real attack events are reproduced by an experimental *** Alibaba's blockchain services and Identity Mixer in Hyperledger Fabric as a case study,the security problems and defense techniques are analyzed and *** last,the future research directions are proposed.

关键词： Security and privacy Blockchain-based services Full stack Architecture perspective Case and experimental study Formal verification

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