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40 results on '"Noah Youngs"'

3. Negative example selection for protein function prediction: the NoGO database.

Author

Noah Youngs, Duncan Penfold-Brown, Richard Bonneau, and Dennis Shasha

Subjects
Biology (General), QH301-705.5
Abstract

Negative examples - genes that are known not to carry out a given protein function - are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html).

Published
2014
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4. An adaptive geometric search algorithm for macromolecular scaffold selection

Author

Richard Bonneau, Tian Jiang, P. Douglas Renfrew, Kevin Drew, Glenn L. Butterfoss, Dennis Shasha, and Noah Youngs

Subjects
0301 basic medicine, Models, Molecular, Protein Folding, Peptidomimetic, Computer science, Protein Conformation, Protein Engineering, Biochemistry, 01 natural sciences, octree, Protein structure, Search algorithm, foldamer, Catalytic Domain, enzyme design, Side chain, Methods, computer.programming_language, chemistry.chemical_classification, 0303 health sciences, Adaptive algorithm, biology, Recombinant Proteins, Metals, Algorithm, Algorithms, Biotechnology, Macromolecule, Protein Binding, Matching (graph theory), Protein design, Bioengineering, 010402 general chemistry, Set (abstract data type), 03 medical and health sciences, loop modeling, Loop modeling, Molecular Biology, Simulation, 030304 developmental biology, business.industry, metal binding, Active site, Computational Biology, Modular design, Python (programming language), 0104 chemical sciences, 030104 developmental biology, Enzyme, chemistry, biology.protein, business, computer
Abstract

A wide variety of protein and peptidomimetic design tasks require matching functional three-dimensional motifs to potential oligomeric scaffolds. Enzyme design, for example, aims to graft active-site patterns typically consisting of 3 to 15 residues onto new protein surfaces. Identifying suitable proteins capable of scaffolding such active-site engraftment requires costly searches to identify protein folds that can provide the correct positioning of side chains to host the desired active site. Other examples of biodesign tasks that require simpler fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications the speed and scaling of geometric search limits downstream design to small patterns. Here we present an adaptive algorithm to searching for side chain take-off angles compatible with an arbitrarily specified functional pattern that enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided but our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design).

Published
2018

5. The mRNA-Bound Proteome and Its Global Occupancy Profile on Protein-Coding Transcripts

Author

Kevin Drew, Noah Youngs, Markus Schueler, Markus Landthaler, Alexandra Vasile, Matthias Selbach, Mathias Munschauer, Emanuel Wyler, Alexander G. Baltz, Björn Schwanhäusser, Christoph Dieterich, Duncan Penfold-Brown, Miha Milek, Richard Bonneau, and Yasuhiro Murakawa

Subjects
Genetics, Proteomics, Messenger RNA, Binding Sites, Sequence analysis, Sequence Analysis, RNA, Quantitative proteomics, RNA, RNA-Binding Proteins, Computational biology, Cell Biology, Biology, Mass Spectrometry, Cell Line, RNA splicing, Proteome, Humans, RNA, Messenger, Binding site, ICLIP, Molecular Biology
Abstract

Protein-RNA interactions are fundamental to core biological processes, such as mRNA splicing, localization, degradation, and translation. We developed a photoreactive nucleotide-enhanced UV crosslinking and oligo(dT) purification approach to identify the mRNA-bound proteome using quantitative proteomics and to display the protein occupancy on mRNA transcripts by next-generation sequencing. Application to a human embryonic kidney cell line identified close to 800 proteins. To our knowledge, nearly one-third were not previously annotated as RNA binding, and about 15% were not predictable by computational methods to interact with RNA. Protein occupancy profiling provides a transcriptome-wide catalog of potential cis-regulatory regions on mammalian mRNAs and showed that large stretches in 3' UTRs can be contacted by the mRNA-bound proteome, with numerous putative binding sites in regions harboring disease-associated nucleotide polymorphisms. Our observations indicate the presence of a large number of mRNA binders with diverse molecular functions participating in combinatorial posttranscriptional gene-expression networks.

Published
2012
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6. An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Author

Yuxiang Jiang, Tal Ronnen Oron, Wyatt T. Clark, Asma R. Bankapur, Daniel D’Andrea, Rosalba Lepore, Christopher S. Funk, Indika Kahanda, Karin M. Verspoor, Asa Ben-Hur, Da Chen Emily Koo, Duncan Penfold-Brown, Dennis Shasha, Noah Youngs, Richard Bonneau, Alexandra Lin, Sayed M. E. Sahraeian, Pier Luigi Martelli, Giuseppe Profiti, Rita Casadio, Renzhi Cao, Zhaolong Zhong, Jianlin Cheng, Adrian Altenhoff, Nives Skunca, Christophe Dessimoz, Tunca Dogan, Kai Hakala, Suwisa Kaewphan, Farrokh Mehryary, Tapio Salakoski, Filip Ginter, Hai Fang, Ben Smithers, Matt Oates, Julian Gough, Petri Törönen, Patrik Koskinen, Liisa Holm, Ching-Tai Chen, Wen-Lian Hsu, Kevin Bryson, Domenico Cozzetto, Federico Minneci, David T. Jones, Samuel Chapman, Dukka BKC, Ishita K. Khan, Daisuke Kihara, Dan Ofer, Nadav Rappoport, Amos Stern, Elena Cibrian-Uhalte, Paul Denny, Rebecca E. Foulger, Reija Hieta, Duncan Legge, Ruth C. Lovering, Michele Magrane, Anna N. Melidoni, Prudence Mutowo-Meullenet, Klemens Pichler, Aleksandra Shypitsyna, Biao Li, Pooya Zakeri, Sarah ElShal, Léon-Charles Tranchevent, Sayoni Das, Natalie L. Dawson, David Lee, Jonathan G. Lees, Ian Sillitoe, Prajwal Bhat, Tamás Nepusz, Alfonso E. Romero, Rajkumar Sasidharan, Haixuan Yang, Alberto Paccanaro, Jesse Gillis, Adriana E. Sedeño-Cortés, Paul Pavlidis, Shou Feng, Juan M. Cejuela, Tatyana Goldberg, Tobias Hamp, Lothar Richter, Asaf Salamov, Toni Gabaldon, Marina Marcet-Houben, Fran Supek, Qingtian Gong, Wei Ning, Yuanpeng Zhou, Weidong Tian, Marco Falda, Paolo Fontana, Enrico Lavezzo, Stefano Toppo, Carlo Ferrari, Manuel Giollo, Damiano Piovesan, Silvio C.E. Tosatto, Angela del Pozo, José M. Fernández, Paolo Maietta, Alfonso Valencia, Michael L. Tress, Alfredo Benso, Stefano Di Carlo, Gianfranco Politano, Alessandro Savino, Hafeez Ur Rehman, Matteo Re, Marco Mesiti, Giorgio Valentini, Joachim W. Bargsten, Aalt D. J. van Dijk, Branislava Gemovic, Sanja Glisic, Vladmir Perovic, Veljko Veljkovic, Nevena Veljkovic, Danillo C. Almeida-e-Silva, Ricardo Z. N. Vencio, Malvika Sharan, Jörg Vogel, Lakesh Kansakar, Shanshan Zhang, Slobodan Vucetic, Zheng Wang, Michael J. E. Sternberg, Mark N. Wass, Rachael P. Huntley, Maria J. Martin, Claire O’Donovan, Peter N. Robinson, Yves Moreau, Anna Tramontano, Patricia C. Babbitt, Steven E. Brenner, Michal Linial, Christine A. Orengo, Burkhard Rost, Casey S. Greene, Sean D. Mooney, Iddo Friedberg, Predrag Radivojac, Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T., Bankapur, Asma R., D’Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S., Kahanda, Indika, Verspoor, Karin M., Ben-Hur, Asa, Koo, Da Chen Emily, Penfold-Brown, Duncan, Shasha, Denni, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed M. E., Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nive, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T., Chapman, Samuel, Bkc, Dukka, Khan, Ishita K., Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amo, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E., Hieta, Reija, Legge, Duncan, Lovering, Ruth C., Magrane, Michele, Melidoni, Anna N., Mutowo-Meullenet, Prudence, Pichler, Klemen, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, Elshal, Sarah, Tranchevent, Léon-Charle, Das, Sayoni, Dawson, Natalie L., Lee, David, Lees, Jonathan G., Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamá, Romero, Alfonso E., Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E., Pavlidis, Paul, Feng, Shou, Cejuela, Juan M., Goldberg, Tatyana, Hamp, Tobia, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio C.E., del Pozo, Angela, Fernández, José M., Maietta, Paolo, Valencia, Alfonso, Tress, Michael L., Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W., van Dijk, Aalt D. J., Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C., Vencio, Ricardo Z. N., Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael J. E., Wass, Mark N., Huntley, Rachael P., Martin, Maria J., O’Donovan, Claire, Robinson, Peter N., Moreau, Yve, Tramontano, Anna, Babbitt, Patricia C., Brenner, Steven E., Linial, Michal, Orengo, Christine A., Rost, Burkhard, Greene, Casey S., Mooney, Sean D., Friedberg, Iddo, Radivojac, Predrag, Friedberg, Iddo [0000-0002-1789-8000], Apollo - University of Cambridge Repository, (ukupan broj autora: 147), Biotechnology and Biological Sciences Research Council (BBSRC), National Science Foundation (Estados Unidos), United States of Department of Health & Human Services, National Natural Science Foundation of China, Natural Sciences and Engineering Research Council (Canadá), São Paulo Research Foundation, Ministerio de Economía y Competitividad (España), Biotechnology and Biological Sciences Research Council (Reino Unido), Katholieke Universiteit Leuven (Bélgica), Newton International Fellowship Scheme of the Royal Society grant, British Heart Foundation, Ministry of Education, Science and Technological Development (Serbia), Office of Biological and Environmental Research (Estados Unidos), Australian Research Council, University of Padua (Italia), Swiss National Science Foundation, Institute of Biotechnology, Computational genomics, and Bioinformatics

Subjects
0301 basic medicine, Computer science, Disease gene prioritization, Protein function prediction, Ecology, Evolution, Behavior and Systematics, Genetics, Cell Biology, 05 Environmental Sciences, 600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit, computer.software_genre, Quantitative Biology - Quantitative Methods, Wiskundige en Statistische Methoden - Biometris, Field (computer science), Laboratorium voor Plantenveredeling, Function (engineering), Databases, Protein, 1183 Plant biology, microbiology, virology, Quantitative Methods (q-bio.QM), media_common, Genetics & Heredity, Settore BIO/11 - BIOLOGIA MOLECOLARE, Ecology, SISTA, 1184 Genetics, developmental biology, physiology, Life Sciences & Biomedicine, Algorithms, Bioinformatics, Evolution, media_common.quotation_subject, BIOINFORMÁTICA, Machine learning, Bottleneck, Set (abstract data type), BIOS Applied Bioinformatics, 03 medical and health sciences, Annotation, Structure-Activity Relationship, Behavior and Systematics, Human Phenotype Ontology, Humans, ddc:610, DISINTEGRIN, Mathematical and Statistical Methods - Biometris, BIOINFORMATICS, 08 Information And Computing Sciences, Science & Technology, business.industry, Research, ADAM, Proteins, Computational Biology, Molecular Sequence Annotation, 06 Biological Sciences, Data set, ONTOLOGY, Plant Breeding, 030104 developmental biology, Gene Ontology, Biotechnology & Applied Microbiology, FOS: Biological sciences, Artificial intelligence, business, computer, Software
Abstract

BACKGROUND: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. RESULTS: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. CONCLUSIONS: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent., We acknowledge the contributions of Maximilian Hecht, Alexander Grün, Julia Krumhoff, My Nguyen Ly, Jonathan Boidol, Rene Schoeffel, Yann Spöri, Jessika Binder, Christoph Hamm and Karolina Worf. This work was partially supported by the following grants: National Science Foundation grants DBI-1458477 (PR), DBI-1458443 (SDM), DBI-1458390 (CSG), DBI-1458359 (IF), IIS-1319551 (DK), DBI-1262189 (DK), and DBI-1149224 (JC); National Institutes of Health grants R01GM093123 (JC), R01GM097528 (DK), R01GM076990 (PP), R01GM071749 (SEB), R01LM009722 (SDM), and UL1TR000423 (SDM); the National Natural Science Foundation of China grants 3147124 (WT) and 91231116 (WT); the National Basic Research Program of China grant 2012CB316505 (WT); NSERC grant RGPIN 371348-11 (PP); FP7 infrastructure project TransPLANT Award 283496 (ADJvD); Microsoft Research/FAPESP grant 2009/53161-6 and FAPESP fellowship 2010/50491-1 (DCAeS); Biotechnology and Biological Sciences Research Council grants BB/L020505/1 (DTJ), BB/F020481/1 (MJES), BB/K004131/1 (AP), BB/F00964X/1 (AP), and BB/L018241/1 (CD); the Spanish Ministry of Economics and Competitiveness grant BIO2012-40205 (MT); KU Leuven CoE PFV/10/016 SymBioSys (YM); the Newton International Fellowship Scheme of the Royal Society grant NF080750 (TN). CSG was supported in part by the Gordon and Betty Moore Foundation’s Data-Driven Discovery Initiative grant GBMF4552. Computational resources were provided by CSC – IT Center for Science Ltd., Espoo, Finland (TS). This work was supported by the Academy of Finland (TS). RCL and ANM were supported by British Heart Foundation grant RG/13/5/30112. PD, RCL, and REF were supported by Parkinson’s UK grant G-1307, the Alexander von Humboldt Foundation through the German Federal Ministry for Education and Research, Ernst Ludwig Ehrlich Studienwerk, and the Ministry of Education, Science and Technological Development of the Republic of Serbia grant 173001. This work was a Technology Development effort for ENIGMA – Ecosystems and Networks Integrated with Genes and Molecular Assemblies (http://enigma.lbl.gov), a Scientific Focus Area Program at Lawrence Berkeley National Laboratory, which is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Biological & Environmental Research grant DE-AC02-05CH11231. ENIGMA only covers the application of this work to microbial proteins. NSF DBI-0965616 and Australian Research Council grant DP150101550 (KMV). NSF DBI-0965768 (ABH). NIH T15 LM00945102 (training grant for CSF). FP7 FET grant MAESTRA ICT-2013-612944 and FP7 REGPOT grant InnoMol (FS). NIH R01 GM60595 (PCB). University of Padova grants CPDA138081/13 (ST) and GRIC13AAI9 (EL). Swiss National Science Foundation grant 150654 and UK BBSRC grant BB/M015009/1 (COD). PRB2 IPT13/0001 - ISCIII-SGEFI / FEDER (JMF)., This is the final version of the article. It first appeared from BioMed Central at http://dx.doi.org/10.1186/s13059-016-1037-6.

Published
2016

7. Positive-Unlabeled Learning in the Face of Labeling Bias

Author

Dennis Shasha, Noah Youngs, and Richard Bonneau

Subjects
Learning classifier system, Computer science, business.industry, Active learning (machine learning), Competitive learning, Supervised learning, Stability (learning theory), Online machine learning, Multi-task learning, Pattern recognition, Semi-supervised learning, Machine learning, computer.software_genre, Ensemble learning, Generalization error, Support vector machine, ComputingMethodologies_PATTERNRECOGNITION, Computational learning theory, Unsupervised learning, Artificial intelligence, Instance-based learning, business, computer
Abstract

Positive-Unlabeled (PU) learning scenarios are a class of semi-supervised learning where only a fraction of the data is labeled, and all available labels are positive. The goal is to assign correct (positive and negative) labels to as much data as possible. Several important learning problems fall into the PU-learning domain, as in many cases the cost and feasibility of obtaining negative examples is prohibitive. In addition to the positive-negative disparity the overall cost of labeling these datasets typically leads to situations where the number of unlabeled examples greatly outnumbers the labeled. Accordingly, we perform several experiments, on both synthetic and real-world datasets, examining the performance of state of the art PU-learning algorithms when there is significant bias in the labeling process. We propose novel PU algorithms and demonstrate that they outperform the current state of the art on a variety of benchmarks. Lastly, we present a methodology for removing the costly parameter-tuning step in a popular PU algorithm.

Published
2015
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8. Negative example selection for protein function prediction: the NoGO database

Author

Richard Bonneau, Noah Youngs, Duncan Penfold-Brown, and Dennis Shasha

Subjects
Topic model, Computer and Information Sciences, Saccharomyces cerevisiae Proteins, Proteome, Computer science, computer.software_genre, Cellular and Molecular Neuroscience, Annotation, Mice, Artificial Intelligence, Databases, Genetic, Genetics, Animals, Humans, Protein function prediction, Molecular Biology, lcsh:QH301-705.5, Ecology, Evolution, Behavior and Systematics, Genome, Ecology, Database, Arabidopsis Proteins, Applied Mathematics, Conditional probability, Computational Biology, Proteins, Biology and Life Sciences, Molecular Sequence Annotation, Gene Annotation, Gene Ontology, Computational Theory and Mathematics, lcsh:Biology (General), Modeling and Simulation, Physical Sciences, Data mining, Heuristics, Open-world assumption, computer, Algorithms, Mathematics, Research Article
Abstract

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html)., Author Summary Many machine learning methods have been applied to the task of predicting the biological function of proteins based on a variety of available data. The majority of these methods require negative examples: proteins that are known not to perform a function, in order to achieve meaningful predictions, but negative examples are often not available. In addition, past heuristic methods for negative example selection suffer from a high error rate. Here, we rigorously compare two novel algorithms against past heuristics, as well as some algorithms adapted from a similar task in text-classification. Through this comparison, performed on several different benchmarks, we demonstrate that our algorithms make significantly fewer mistakes when predicting negative examples. We also provide a database of negative examples for general use in machine learning for protein function prediction (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html).

Published
2014

12. A Study on Blockchain Architecture Design Decisions and Their Security Attacks and Threats.

Author

AHMADJEE, SABREEN, MERA-GÓMEZ, CARLOS, BAHSOON, RAMI, and KAZMAN, RICK

Subjects
ARCHITECTURAL design, DISRUPTIVE innovations, BLOCKCHAINS, SYSTEMS software, SECURITY management, SECURITY classification (Government documents)
Abstract

Blockchain is a disruptive technology intended to implement secure decentralised distributed systems, in which transactional data can be shared, stored, and verified by participants of the system without needing a central authentication/verification authority. Blockchain-based systems have several architectural components and variants, which architects can leverage to build secure software systems. However, there is a lack of studies to assist architects in making architecture design and configuration decisions for blockchain-based systems. This knowledge gap may increase the chance of making unsuitable design decisions and producing configurations prone to potential security risks. To address this limitation, we report our comprehensive systematic literature review to derive a taxonomy of commonly used architecture design decisions in blockchainbased systems.We map each of these decisions to potential security attacks and their posed threats. MITRE’s attack tactic categories and Microsoft STRIDE threat modeling are used to systematically classify threats and their associated attacks to identify potential attacks and threats in blockchain-based systems. Our mapping approach aims to guide architects to make justifiable design decisions that will result in more secure implementations. [ABSTRACT FROM AUTHOR]

Published
2022
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13. Crypto Coin Offerings and the Freedom of Expression.

Author

Travis, Hannibal

Subjects
FREEDOM of expression, COINS, BANKING laws, ARTIFICIAL intelligence, INDUSTRIAL management
Abstract

The article focuses on privacy-enhancing networks of software resources power massive digital economies in the form of crypto coin protocols and their users. Topics include the Telegram Group led by the founder of social media giant VKontakte, Telegram has transitioned Gram into a private offering restricted to accredited wealthy investors, and the Securities and Exchange Commission has enjoined any offer to sell Grams not registered as securities.

Published
2021

14. Account Guarantee Scheme: Making Anonymous Accounts Supervised in Blockchain.

Author

LICHEN CHENG, JIQIANG LIU, YI JIN, YIDONG LI, and WEI WANG

Subjects
SURETYSHIP & guaranty, BLOCKCHAINS, ANONYMITY
Abstract

In blockchain networks, reaching effective supervision while maintaining anonymity to the public has been an ongoing challenge. In existing solutions, certification authorities need to record all pairs of identities and pseudonyms, which is demanding and costly. This article proposed an account guarantee scheme to realize feasible supervision for existing anonymous blockchain networks with lower storage costs. Users are able to guarantee anonymous accounts with account guarantee key pairs generated from certificated polynomial functions, which inherently maintains one-to-n mapping certifications. Single or limited account guarantee key pairs do not leak privacy. Victims are able to request TCs to screen a cheater or disclose a cheater with enough fraud transactions by themselves. Detailed security and privacy analysis showed that the account guarantee scheme preserves user privacy and realizes feasible supervision. Experimental results demonstrated that the account guarantee scheme is efficient and practical. [ABSTRACT FROM AUTHOR]

Published
2021
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15. Towards region-specific propagation of protein functions.

Author

Koo, Da Chen Emily and Bonneau, Richard

Subjects
PROTEINS, BIOINFORMATICS, GENE ontology, PROTEOMICS, GENE expression
Abstract

Motivation Due to the nature of experimental annotation, most protein function prediction methods operate at the protein-level, where functions are assigned to full-length proteins based on overall similarities. However, most proteins function by interacting with other proteins or molecules, and many functional associations should be limited to specific regions rather than the entire protein length. Most domain-centric function prediction methods depend on accurate domain family assignments to infer relationships between domains and functions, with regions that are unassigned to a known domain-family left out of functional evaluation. Given the abundance of residue-level annotations currently available, we present a function prediction methodology that automatically infers function labels of specific protein regions using protein-level annotations and multiple types of region-specific features. Results We apply this method to local features obtained from InterPro, UniProtKB and amino acid sequences and show that this method improves both the accuracy and region-specificity of protein function transfer and prediction. We compare region-level predictive performance of our method against that of a whole-protein baseline method using proteins with structurally verified binding sites and also compare protein-level temporal holdout predictive performances to expand the variety and specificity of GO terms we could evaluate. Our results can also serve as a starting point to categorize GO terms into region-specific and whole-protein terms and select prediction methods for different classes of GO terms. Availability and implementation The code and features are freely available at: https://github.com/ek1203/rsfp. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2019
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16. adaptive geometric search algorithm for macromolecular scaffold selection.

Author

Jiang, Tian, Renfrew, P Douglas, Drew, Kevin, Youngs, Noah, Butterfoss, Glenn L, Bonneau, Richard, and Shasha, Den Nis

Subjects
PROTEIN folding, SEARCH algorithms, MACROMOLECULAR dynamics, PEPTIDOMIMETICS, BINDING sites
Abstract

A wide variety of protein and peptidomimetic design tasks require matching functional 3D motifs to potential oligomeric scaffolds. For example, during enzyme design, one aims to graft active-site patterns—typically consisting of 3–15 residues—onto new protein surfaces. Identifying protein scaffolds suitable for such active-site engraftment requires costly searches for protein folds that provide the correct side chain positioning to host the desired active site. Other examples of biodesign tasks that require similar fast exact geometric searches of potential side chain positioning include mimicking binding hotspots, design of metal binding clusters and the design of modular hydrogen binding networks for specificity. In these applications, the speed and scaling of geometric searches limits the scope of downstream design to small patterns. Here, we present an adaptive algorithm capable of searching for side chain take-off angles, which is compatible with an arbitrarily specified functional pattern and which enjoys substantive performance improvements over previous methods. We demonstrate this method in both genetically encoded (protein) and synthetic (peptidomimetic) design scenarios. Examples of using this method with the Rosetta framework for protein design are provided. Our implementation is compatible with multiple protein design frameworks and is freely available as a set of python scripts (https://github.com/JiangTian/adaptive-geometric-search-for-protein-design). [ABSTRACT FROM AUTHOR]

Published
2018
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21. MOVING BEYOND BITCOIN TO AN ENDOGENOUS THEORY OF DECENTRALIZED LEDGER TECHNOLOGY REGULATION: AN INITIAL PROPOSAL.

Author

REYES, CARLA L.

Subjects
ACCOUNT books, BITCOIN, COMPARATIVE law, FINANCIAL services industry, DIGITAL currency, LAW
Abstract

The article focuses on the decentralized ledger technology ecosystem such as bitcoin payments. It mentions that the endogenous theory of decentralized ledger technology regulation from concepts found in economic regulation, international development, comparative law, and financial regulation. It also mentions that ex ante and ex post regulatory dichotomy by building compliance into the protocol.

Published
2016

22. Negative Example Selection for Protein Function Prediction: The NoGO Database.

Author

Youngs, Noah, Penfold-Brown, Duncan, Bonneau, Richard, and Shasha, Dennis

Subjects
PROTEIN analysis, PREDICTION models, NOGO protein, DATABASES, MACHINE learning
Abstract

Negative examples – genes that are known not to carry out a given protein function – are rarely recorded in genome and proteome annotation databases, such as the Gene Ontology database. Negative examples are required, however, for several of the most powerful machine learning methods for integrative protein function prediction. Most protein function prediction efforts have relied on a variety of heuristics for the choice of negative examples. Determining the accuracy of methods for negative example prediction is itself a non-trivial task, given that the Open World Assumption as applied to gene annotations rules out many traditional validation metrics. We present a rigorous comparison of these heuristics, utilizing a temporal holdout, and a novel evaluation strategy for negative examples. We add to this comparison several algorithms adapted from Positive-Unlabeled learning scenarios in text-classification, which are the current state of the art methods for generating negative examples in low-density annotation contexts. Lastly, we present two novel algorithms of our own construction, one based on empirical conditional probability, and the other using topic modeling applied to genes and annotations. We demonstrate that our algorithms achieve significantly fewer incorrect negative example predictions than the current state of the art, using multiple benchmarks covering multiple organisms. Our methods may be applied to generate negative examples for any type of method that deals with protein function, and to this end we provide a database of negative examples in several well-studied organisms, for general use (The NoGO database, available at: bonneaulab.bio.nyu.edu/nogo.html). [ABSTRACT FROM AUTHOR]

Published
2014
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24. A Farm Family on Long Island's North Fork : The Lost World of the Hallocks and Their Sound Avenue Community

Author

Richard A. Wines and Richard A. Wines

Subjects
Hallockville Museum Farm--History
Abstract

In A Farm Family on Long Island's North Fork, Richard A. Wines traces the history of a vital agricultural community on the North Fork of Long Island through the story of the last family to live in the old Homestead at the Hallockville Museum Farm. For well over two centuries, community members were almost all descendants of the same group of seventeenth-century Puritan founders. Yet, despite their shared heritage and complex interrelationships, cultural wars raged. Family members and the community divided bitterly on issue after issue, ranging from whether to allow a melodeon into the church to supporting abolitionism. The community weathered many changes—the Civil War, the emergence of new agricultural technologies, the arrival of Eastern European immigrants, even an attempt to build a string of nuclear power plants in the twentieth century. Wines's deep dives into one community's history uncover stories about slavery, racism, and prejudice that many have chosen to forget, as well as stories of compassion or human tragedy we want to remember. A Farm Family on Long Island's North Fork will appeal to those interested in Long Island regional history and the larger history of rural communities throughout New York and the United States.

Published
2024

25. Intelligent Distributed Computing XV

Author

Lars Braubach, Kai Jander, Costin Bădică, Lars Braubach, Kai Jander, and Costin Bădică

Subjects
Computational intelligence, Artificial intelligence
Abstract

This book includes the latest research in the diverse field of intelligent distributed computing, covering a multitude of aspects in both distributed computing and intelligent systems. It includes contributions in machine learning, distributed systems & agents, text- and research-centric applications, social systems, and smart cities. It was written by leading experts in the field, who presented their work as part of the 15th International Symposium on Intelligent Distributed Computing (IDC 2022).

Published
2023

26. Cryptocurrency: Policy Issues, Financial Implications, and Security Risks

Author

Edward J. McCallum and Edward J. McCallum

Subjects
Digital currency, Cryptocurrencies
Abstract

Cryptocurrencies are digital money in electronic payment systems that generally do not require government backing or the involvement of an intermediary, such as a bank. Instead, users of the system validate payments using certain protocols. Since the 2008 invention of the first cryptocurrency, Bitcoin, cryptocurrencies have proliferated. In recent years, they experienced a rapid increase and subsequent decrease in value. One estimate found that, as of March 2020, there were more than 5,100 different cryptocurrencies worth about $231 billion.

Published
2022

27. Bitcoin Cryptocurrency Blockchain : All You Need to Know About the Metaverse.Web 3.0. DEFI. NFTs

Author

Cecil (CJ) John and Cecil (CJ) John

Subjects
Blockchains (Databases), Electronic commerce, Bitcoin
Abstract

BITCOIN, CRYPTOCURRENCY, BLOCKCHAIN, NFTS, DEFI, METAVERSE— THESE WORDS DESCRIBE THE NEW INDUSTRIAL REVOLUTION AND THE BIRTH OF RADICALLY DISRUPTIVE DIGITAL CURRENCIES. WHAT DO THEY MEAN? What do blockchain, bitcoin and cryptocurrencies mean for your financial future? Are cryptocurrencies just high-technology scams, or are they potentially lucrative sources of income? What are the implications of these cutting-edge technologies for your job, career, and prosperity? Blockchain and Cryptocurrencies can be immensely profitable, but you have to understand these technologies. In this book, Cecil (CJ) John introduces you to this new digital era in a simple, reader-friendly way. This enjoyable and authoritative guide will help you unravel the mysteries of this fast-growing new economy, including about this mysterious but ever more influential part of the economy, including answers to questions like these: What is Cryptocurrency? What are the best Cryptocurrencies for investing? What are the most effective ways to invest in Cryptocurrencies? What are the career opportunities in Blockchain and Cryptocurrency? What are the business opportunities in Blockchain and Cryptocurrency? What are the fundamentals of Blockchain? What is decentralized finance, and how can you profit from it? What are NFTS, and how can you create one? • What is Web 3.0 and why is it important? What is the metaverse and what's Blockchain got to do with it? Will the government regulate Blockchain and Cryptocurrency? What is the relationship between digital money and morality?There's even more. This book shows how these revolutionary new technologies and digital currencies can transform society and economics, giving people more financial security and more say in creating and distributing money. Cecil (CJ) John is a chartered architect, computer scientist, and author. He is the chief executive officer of virtualdeveloper.com, LLC, an information technology firm that has worked with some of the largest organizations in the world.

Published
2022

28. Blockchain Technology: Advances in Research and Applications

Author

Eva R Porras and Eva R Porras

Subjects
Electronic funds transfers, Blockchains (Databases)--Economic aspects, Application software--Development, Business enterprises--Technological innovations, Banks and banking--Technological innovations
Abstract

Nakamoto's 2008 publication of the Bitcoin protocol started a technological and economic revolution. Now, more than 10,000 digital payment brands in the markets claim to be backed up by distributed ledger technologies (DTLs) or blockchains. This volume compares the characteristics of these technologies while it brings clarity to the different aspects of the ecosystem.

Published
2022

29. Proceedings of the Third International Conference on Computational Intelligence and Informatics : ICCII 2018

Author

K. Srujan Raju, A. Govardhan, B. Padmaja Rani, R. Sridevi, M. Ramakrishna Murty, K. Srujan Raju, A. Govardhan, B. Padmaja Rani, R. Sridevi, and M. Ramakrishna Murty

Subjects
Computational intelligence, Telecommunication, Bioinformatics
Abstract

This book features high-quality papers presented at the International Conference on Computational Intelligence and Informatics (ICCII 2018), which was held on 28–29 December 2018 at the Department of Computer Science and Engineering, JNTUH College of Engineering, Hyderabad, India. The papers focus on topics such as data mining, wireless sensor networks, parallel computing, image processing, network security, MANETS, natural language processing and Internet of things.

Published
2020

30. Blockchain Technology : Fundamentals, Applications, and Case Studies

Author

E. Golden Julie, J. Jesu Vedha Nayahi, Noor Zaman Jhanjhi, E. Golden Julie, J. Jesu Vedha Nayahi, and Noor Zaman Jhanjhi

Subjects
Blockchains (Databases)
Abstract

This book presents a detailed exploration of adaption and implementation, as well as a 360-degree view spectrum of blockchain technologies in real-world business applications. Blockchain is gaining momentum in all sectors. This book offers a collection of protocol standards, issues, security improvements, applicability, features, and types of cryptocurrency in processing and through 5G technology. The book covers the evolution of blockchain from fundamental theories to present forms. It offers diversified business applications with usable case studies and provides successful implementations in cloud/edge computing, smart city, and IoT. The book emphasizes the advances and cutting-edge technologies along with the different tools and platforms.The primary audience for this book includes industry experts, researchers, graduates and under graduates, practitioners, and business managers who are engaged in blockchain and IoT-related technologies.

Published
2020

31. Blockchain and the Law : The Rule of Code

Author

Primavera De Filippi, Aaron Wright, Primavera De Filippi, and Aaron Wright

Subjects
Internet in public administration, Data encryption (Computer science), Blockchains (Databases), Technology and law
Abstract

“Blockchains will matter crucially; this book, beautifully and clearly written for a wide audience, powerfully demonstrates how.”—Lawrence Lessig“Attempts to do for blockchain what the likes of Lawrence Lessig and Tim Wu did for the Internet and cyberspace—explain how a new technology will upend the current legal and social order… Blockchain and the Law is not just a theoretical guide. It's also a moral one.”—FortuneBitcoin has been hailed as an Internet marvel and decried as the preferred transaction vehicle for criminals. It has left nearly everyone without a computer science degree confused: how do you “mine” money from ones and zeros?The answer lies in a technology called blockchain. A general-purpose tool for creating secure, decentralized, peer-to-peer applications, blockchain technology has been compared to the Internet in both form and impact. Blockchains are being used to create “smart contracts,” to expedite payments, to make financial instruments, to organize the exchange of data and information, and to facilitate interactions between humans and machines. But by cutting out the middlemen, they run the risk of undermining governmental authorities'ability to supervise activities in banking, commerce, and the law. As this essential book makes clear, the technology cannot be harnessed productively without new rules and new approaches to legal thinking.“If you…don't ‘get'crypto, this is the book-length treatment for you.”—Tyler Cowen, Marginal Revolution“De Filippi and Wright stress that because blockchain is essentially autonomous, it is inflexible, which leaves it vulnerable, once it has been set in motion, to the sort of unforeseen consequences that laws and regulations are best able to address.”—James Ryerson, New York Times Book Review

Published
2018

32. The End of Money : The Story of Bitcoin, Cryptocurrencies and the Blockchain Revolution

Author

New Scientist and New Scientist

Subjects
Money--History--21st century, Bitcoin, Electronic funds transfers
Abstract

The End of Money is an essential introduction to cryptocurrencies and the blockchain revolution. On this journey you'll discover how this staggering new technology has the potential to enable an ultra-libertarian society beyond government control.Murder for hire. Drug trafficking. Embezzlement. Money laundering. These might sound like plot lines of a thriller, but they are true stories from the short history of cryptocurrencies - digital currencies conceived by computer hackers and cryptographers that represent a completely new sort of financial transaction that could soon become mainstream. The most famous - or infamous - cryptocurrency is bitcoin. But look beyond its tarnished reputation and something much shinier emerges. The technology that underlies bitcoin and other cryptocurrencies - the blockchain - is hailed as the greatest advancement since the invention of the internet. It is now moving away from being the backbone for a digital currency and making inroads into other core concepts of society: identity, ownership and even the rule of law.The End of Money is your essential introduction to this transformative new technology that has governments, entrepreneurs and forward-thinking people from all walks of life sitting up and taking notice.ABOUT THE SERIESNew Scientist Instant Expert books are definitive and accessible entry points to the most important subjects in science; subjects that challenge, attract debate, invite controversy and engage the most enquiring minds. Designed for curious readers who want to know how things work and why, the Instant Expert series explores the topics that really matter and their impact on individuals, society, and the planet, translating the scientific complexities around us into language that's open to everyone, and putting new ideas and discoveries into perspective and context.

Published
2017

33. Semantic Data Mining : An Ontology-based Approach

Author

LAWRYNOWICZ, A. and LAWRYNOWICZ, A.

Subjects
Data mining
Abstract

Ontologies are now increasingly used to integrate, and organize data and knowledge, particularly in data and knowledge-intensive applications in both research and industry. The book is devoted to semantic data mining – a data mining approach where domain ontologies are used as background knowledge, and where the new challenge is to mine knowledge encoded in domain ontologies and knowledge graphs, rather than only purely empirical data. The introductory chapters of the book provide theoretical foundations of both data mining and ontology representation. Taking a unified perspective, the book then covers several methods for semantic data mining, addressing tasks such as pattern mining, classification and similarity-based approaches. It attempts to provide state-of-the-art answers to specific challenges and peculiarities of data mining with use of ontologies, in particular: How to deal with incompleteness of knowledge and the so-called Open World Assumption? What is a truly “semantic” similarity measure? The book contains several chapters with examples of applications of semantic data mining. The examples start from a scenario with moderate use of lightweight ontologies for knowledge graph enrichment and end with a full-fledged scenario of an intelligent knowledge discovery assistant using complex domain ontologies for meta-mining, i.e., an ontology-based meta-learning approach to full data mining processes. The book is intended for researchers in the fields of semantic technologies, knowledge engineering, data science, and data mining, and developers of knowledge-based systems and applications.

Published
2017

34. Bitcoin and Blockchain Security

Author

Karame, Ghassan O., Androulaki, Elli, Karame, Ghassan O., and Androulaki, Elli

Subjects
Electronic funds transfers--Security measures, Bitcoin, Electronic commerce
Abstract

There is a lot of buzz about Bitcoin and Blockchain lately, our expert authors will help to answer some imperative questions about the security involved in this new digital asset and ledger. This comprehensive new resource presents a thorough overview and analysis of the security and privacy provisions of Bitcoin and its underlying blockchain clients. This book goes beyond the analysis of reported vulnerabilities of Bitcoin, evaluating a number of countermeasures to deter threats on the system. Readers are given concrete solutions and recommendations on the best practices to use when relying on Bitcoin as a payment method. This resource provides a clear explanation of assumptions governing the security of Bitcoin, including the scalability measures adopted in Bitcoin, privacy for clients, and the proper means of securing Bitcoin wallets. Readers learn how the security and privacy provisions of other blockchain technologies compare to Bitcoin and the security lessons learned after extensive research of Bitcoin since the inception of the currency.

Published
2016

36. DOJ RELEASES FEBRUARY VIOLENT CRIME PROSECUTION RECAP

Subjects
United States. Department of Justice, Attorneys general, Violence, News, opinion and commentary
Abstract

DOVER, DE -- The following information was released by the State of Delaware: Attorney General Kathy Jennings announced Friday that the Department of Justice charged 130 gun offenders and secured [...]

Published
2022

37. An 'Organic' Menu? Well, Not Entirely

Author

Krishna, Priya

Subjects
United States. Department of Agriculture -- Laws, regulations and rules, Organic foods -- Forecasts and trends -- Laws, regulations and rules, Restaurant industry -- Forecasts and trends -- Laws, regulations and rules, Government regulation, Market trend/market analysis, General interest, News, opinion and commentary
Abstract

About four years ago, Gil Rosenberg started eating at Bareburger, an international restaurant chain, after undergoing surgery that left him prone to infection and more inclined to eat organic meat. [...]

Published
2018

38. When the Menu Says 'Organic,' but Not All the Food Is

Author

Krishna, Priya

Subjects
United States. Department of Agriculture, Organic foods, Chain restaurants, General interest
Abstract

Byline: PRIYA KRISHNA About four years ago, Gil Rosenberg started eating at Bareburger, an international restaurant chain, after undergoing surgery that left him prone to infection and more inclined to [...]

Published
2018

40. Tough exit

Subjects
General interest, News, opinion and commentary
Abstract

Jan. 31--CLAYTON -- A sensational season for the Fike High wrestling team ended with a thud in the opening round of the North Carolina High School Athletic Association 3-A Duals [...]

Published
2018

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