scholarly journals Large-Scale de novo Oligonucleotide Synthesis for Whole-Genome Synthesis and Data Storage: Challenges and Opportunities

2021 ◽  
Vol 9 ◽  
Author(s):  
Li-Fu Song ◽  
Zheng-Hua Deng ◽  
Zi-Yi Gong ◽  
Lu-Lu Li ◽  
Bing-Zhi Li
Keyword(s):  
Data Storage ◽  
Large Scale ◽  
De Novo ◽  
Special Focus ◽  
Oligonucleotide Synthesis ◽  
Phosphoramidite Chemistry ◽  
Challenges And Opportunities ◽  
The Status ◽  
Remarkable Progress ◽  
Enzymatic Methods

Over the past decades, remarkable progress on phosphoramidite chemistry-based large-scale de novo oligonucleotide synthesis has been achieved, enabling numerous novel and exciting applications. Among them, de novo genome synthesis and DNA data storage are striking. However, to make these two applications more practical, the synthesis length, speed, cost, and throughput require vast improvements, which is a challenge to be met by the phosphoramidite chemistry. Harnessing the power of enzymes, the recently emerged enzymatic methods provide a competitive route to overcome this challenge. In this review, we first summarize the status of large-scale oligonucleotide synthesis technologies including the basic methodology and large-scale synthesis approaches, with special focus on the emerging enzymatic methods. Afterward, we discuss the opportunities and challenges of large-scale oligonucleotide synthesis on de novo genome synthesis and DNA data storage respectively.

Comparison Study of Different NoSQL and Cloud Paradigm for Better Data Storage Technology

2018 ◽  
pp. 312-343
Author(s):  
Pankaj Lathar ◽  
K. G. Srinivasa ◽  
Abhishek Kumar ◽  
Nabeel Siddiqui
Keyword(s):  
Cloud Computing ◽  
Data Management ◽  
Data Storage ◽  
High Performance ◽  
Large Scale ◽  
Web Based ◽  
Storage Technology ◽  
Data Store ◽  
Challenges And Opportunities ◽  
User Data

Advancements in web-based technology and the proliferation of sensors and mobile devices interacting with the internet have resulted in immense data management requirements. These data management activities include storage, processing, demand of high-performance read-write operations of big data. Large-scale and high-concurrency applications like SNS and search engines have appeared to be facing challenges in using the relational database to store and query dynamic user data. NoSQL and cloud computing has emerged as a paradigm that could meet these requirements. The available diversity of existing NoSQL and cloud computing solutions make it difficult to comprehend the domain and choose an appropriate solution for a specific business task. Therefore, this chapter reviews NoSQL and cloud-system-based solutions with the goal of providing a perspective in the field of data storage technology/algorithms, leveraging guidance to researchers and practitioners to select the best-fit data store, and identifying challenges and opportunities of the paradigm.

BIG DATA PROCESSING: BIG CHALLENGES AND OPPORTUNITIES

2012 ◽  
Vol 13 (03n04) ◽  
pp. 1250009 ◽  
Author(s):  
CHANGQING JI ◽  
YU LI ◽  
WENMING QIU ◽  
YINGWEI JIN ◽  
YUJIE XU ◽  
...  
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Management ◽  
Data Storage ◽  
Large Scale ◽  
Distributed Applications ◽  
Big Data Processing ◽  
Cloud Data ◽  
Management Platform ◽  
Challenges And Opportunities

With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing techniques from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including definition of big data, big data management platform, big data service models, distributed file system, data storage, data virtualization platform and distributed applications. Following the MapReduce parallel processing framework, we introduce some MapReduce optimization strategies reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

scholarly journals Proteomics in Forensic Analysis: Applications for Human Samples

2021 ◽  
Vol 11 (8) ◽  
pp. 3393
Author(s):  
Van-An Duong ◽  
Jong-Moon Park ◽  
Hee-Joung Lim ◽  
Hookeun Lee
Keyword(s):  
Forensic Science ◽  
Large Scale ◽  
De Novo ◽  
Genomic Analysis ◽  
Forensic Analysis ◽  
Body Fluids ◽  
Special Focus ◽  
Holistic View ◽  
Human Samples ◽  
Wide Range

Proteomics, the large-scale study of all proteins of an organism or system, is a powerful tool for studying biological systems. It can provide a holistic view of the physiological and biochemical states of given samples through identification and quantification of large numbers of peptides and proteins. In forensic science, proteomics can be used as a confirmatory and orthogonal technique for well-built genomic analyses. Proteomics is highly valuable in cases where nucleic acids are absent or degraded, such as hair and bone samples. It can be used to identify body fluids, ethnic group, gender, individual, and estimate post-mortem interval using bone, muscle, and decomposition fluid samples. Compared to genomic analysis, proteomics can provide a better global picture of a sample. It has been used in forensic science for a wide range of sample types and applications. In this review, we briefly introduce proteomic methods, including sample preparation techniques, data acquisition using liquid chromatography-tandem mass spectrometry, and data analysis using database search, spectral library search, and de novo sequencing. We also summarize recent applications in the past decade of proteomics in forensic science with a special focus on human samples, including hair, bone, body fluids, fingernail, muscle, brain, and fingermark, and address the challenges, considerations, and future developments of forensic proteomics.

Forest Management In Mongolia – A Review Of Challenges And Lessons Learned With Special Reference To Degradation And Deforestation

2019 ◽  
Vol 12 (3) ◽  
pp. 133-166 ◽  
Author(s):  
Alexander Gradel ◽  
Gerelbaatar Sukhbaatar ◽  
Daniel Karthe ◽  
Hoduck Kang
Keyword(s):  
Forest Management ◽  
Land Management ◽  
Management Practices ◽  
Forest Health ◽  
Hydrological Regime ◽  
Lessons Learned ◽  
Ecosystem Functions ◽  
Special Focus ◽  
Driven System ◽  
The Status

The natural conditions, climate change and socio-economic challenges related to the transformation from a socialistic society towards a market-driven system make the implementation of sustainable land management practices in Mongolia especially complicated. Forests play an important role in land management. In addition to providing resources and ecosystem functions, Mongolian forests protect against land degradation.We conducted a literature review of the status of forest management in Mongolia and lessons learned, with special consideration to halting deforestation and degradation. We grouped our review into seven challenges relevant to developing regionally adapted forest management systems that both safeguard forest health and consider socio-economic needs. In our review, we found that current forest management in Mongolia is not always sustainable, and that some practices lack scientific grounding. An overwhelming number of sources noticed a decrease in forest area and quality during the last decades, although afforestation initiatives are reported to have increased. We found that they have had, with few exceptions, only limited success. During our review, however, we found a number of case studies that presented or proposed promising approaches to (re-)establishing and managing forests. These studies are further supported by a body of literature that examines how forest administration, and local participation can be modified to better support sustainable forestry. Based on our review, we conclude that it is necessary to integrate capacity development and forest research into holistic initiatives. A special focus should be given to the linkages between vegetation cover and the hydrological regime.

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

A Target-Based Method for Designing Heterochiral Cyclic Peptide Binders: De Novo Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
Cyclic Peptide ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

Target-Templated de novo Design of Macrocyclic D-/L-Peptides: Inhibitors of the PD-1/PD-L1 Interaction

2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt
Keyword(s):  
Protein Interactions ◽  
Cyclic Peptides ◽  
General Framework ◽  
Large Scale ◽  
De Novo ◽  
Inhibitory Effect ◽  
Original Text ◽  
Protein Protein Interactions ◽  
Retraction Notice ◽  
Pharmaceutical Properties

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>

scholarly journals Remote Sensing Methods for the Biophysical Characterization of Protected Areas Globally: Challenges and Opportunities

2021 ◽  
Vol 10 (6) ◽  
pp. 384
Author(s):  
Javier Martínez-López ◽  
Bastian Bertzky ◽  
Simon Willcock ◽  
Marine Robuchon ◽  
María Almagro ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Large Scale ◽  
Anthropogenic Activities ◽  
Global Scale ◽  
Area Network ◽  
Biophysical Characterization ◽  
Challenges And Opportunities ◽  
Scale Characterization

Protected areas (PAs) are a key strategy to reverse global biodiversity declines, but they are under increasing pressure from anthropogenic activities and concomitant effects. Thus, the heterogeneous landscapes within PAs, containing a number of different habitats and ecosystem types, are in various degrees of disturbance. Characterizing habitats and ecosystems within the global protected area network requires large-scale monitoring over long time scales. This study reviews methods for the biophysical characterization of terrestrial PAs at a global scale by means of remote sensing (RS) and provides further recommendations. To this end, we first discuss the importance of taking into account the structural and functional attributes, as well as integrating a broad spectrum of variables, to account for the different ecosystem and habitat types within PAs, considering examples at local and regional scales. We then discuss potential variables, challenges and limitations of existing global environmental stratifications, as well as the biophysical characterization of PAs, and finally offer some recommendations. Computational and interoperability issues are also discussed, as well as the potential of cloud-based platforms linked to earth observations to support large-scale characterization of PAs. Using RS to characterize PAs globally is a crucial approach to help ensure sustainable development, but it requires further work before such studies are able to inform large-scale conservation actions. This study proposes 14 recommendations in order to improve existing initiatives to biophysically characterize PAs at a global scale.

scholarly journals Democratizing ownership and participation in the 4th Industrial Revolution: challenges and opportunities in cellular agriculture

2021 ◽  
Author(s):  
Robert M. Chiles ◽  
Garrett Broad ◽  
Mark Gagnon ◽  
Nicole Negowetti ◽  
Leland Glenna ◽  
...  
Keyword(s):  
Business Models ◽  
Industrial Revolution ◽  
Cultured Cells ◽  
Advanced Materials ◽  
High Stakes ◽  
Digital Platforms ◽  
Challenges And Opportunities ◽  
The Status ◽  
Political Economic ◽  
Industry Sectors

AbstractThe emergence of the “4th Industrial Revolution,” i.e. the convergence of artificial intelligence, the Internet of Things, advanced materials, and bioengineering technologies, could accelerate socioeconomic insecurities and anxieties or provide beneficial alternatives to the status quo. In the post-Covid-19 era, the entities that are best positioned to capitalize on these innovations are large firms, which use digital platforms and big data to orchestrate vast ecosystems of users and extract market share across industry sectors. Nonetheless, these technologies also have the potential to democratize ownership, broaden political-economic participation, and reduce environmental harms. We articulate the potential sociotechnical pathways in this high-stakes crossroads by analyzing cellular agriculture, an exemplary 4th Industrial Revolution technology that synergizes computer science, biopharma, tissue engineering, and food science to grow cultured meat, dairy, and egg products from cultured cells and/or genetically modified yeast. Our exploration of this space involved multi-sited ethnographic research in both (a) the cellular agriculture community and (b) alternative economic organizations devoted to open source licensing, member-owned cooperatives, social financing, and platform business models. Upon discussing how these latter approaches could potentially facilitate alternative sociotechnical pathways in cellular agriculture, we reflect upon the broader implications of this work with respect to the 4th Industrial Revolution and the enduring need for public policy reform.

Large-scale Data Integration for Facilities Analytics: Challenges and Opportunities

2020 ◽  
Author(s):  
Balaje T. Thumati ◽  
Halasya Siva Subramania ◽  
Rajeev Shastri ◽  
Karthik Kalyana Kumar ◽  
Nicole Hessner ◽  
...  
Keyword(s):  
Data Integration ◽  
Large Scale ◽  
Large Scale Data ◽  
Challenges And Opportunities ◽  
Scale Data
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