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The proteome landscape of the kingdoms of life 期刊论文
NATURE, 2020
作者:  Arzi, Anat;  Rozenkrantz, Liron;  Gorodisky, Lior;  Rozenkrantz, Danit;  Holtzman, Yael;  Ravia, Aharon;  Bekinschtein, Tristan A.;  Galperin, Tatyana;  Krimchansky, Ben-Zion;  Cohen, Gal;  Oksamitni, Anna;  Aidinoff, Elena;  Sacher, Yaron;  Sobel, Noam
收藏  |  浏览/下载:14/0  |  提交时间:2020/07/03

Proteins carry out the vast majority of functions in all biological domains, but for technological reasons their large-scale investigation has lagged behind the study of genomes. Since the first essentially complete eukaryotic proteome was reported(1), advances in mass-spectrometry-based proteomics(2)have enabled increasingly comprehensive identification and quantification of the human proteome(3-6). However, there have been few comparisons across species(7,8), in stark contrast with genomics initiatives(9). Here we use an advanced proteomics workflow-in which the peptide separation step is performed by a microstructured and extremely reproducible chromatographic system-for the in-depth study of 100 taxonomically diverse organisms. With two million peptide and 340,000 stringent protein identifications obtained in a standardized manner, we double the number of proteins with solid experimental evidence known to the scientific community. The data also provide a large-scale case study for sequence-based machine learning, as we demonstrate by experimentally confirming the predicted properties of peptides fromBacteroides uniformis. Our results offer a comparative view of the functional organization of organisms across the entire evolutionary range. A remarkably high fraction of the total proteome mass in all kingdoms is dedicated to protein homeostasis and folding, highlighting the biological challenge of maintaining protein structure in all branches of life. Likewise, a universally high fraction is involved in supplying energy resources, although these pathways range from photosynthesis through iron sulfur metabolism to carbohydrate metabolism. Generally, however, proteins and proteomes are remarkably diverse between organisms, and they can readily be explored and functionally compared at www.proteomesoflife.org.


  
Heterogeneities in energy technological learning: Evidence from the US electricity industry 期刊论文
ENERGY POLICY, 2019, 132: 1034-1049
作者:  Shittu, Ekundayo;  Kamdem, Bruno G.;  Weigelt, Carmen
收藏  |  浏览/下载:12/0  |  提交时间:2019/11/27
Technological learning  Policy  Knowledge acquisition  Electricity industry  
From fossil fuels to renewables: An analysis of long-term scenarios considering technological learning 期刊论文
ENERGY POLICY, 2019, 127: 134-146
作者:  Handayani, Kamia;  Krozer, Yoram;  Filatova, Tatiana
收藏  |  浏览/下载:14/0  |  提交时间:2019/11/26
Renewable energy  Technological learning  LEAP  Climate change mitigation  Indonesia  
Interactions between social learning and technological learning in electric vehicle futures 期刊论文
ENVIRONMENTAL RESEARCH LETTERS, 2018, 13 (12)
作者:  Edelenbosch, O. Y.;  McCollum, David L.;  Pettifor, Hazel;  Wilson, Charlie;  van Vuuren, Detlef P.
收藏  |  浏览/下载:9/0  |  提交时间:2019/04/09
transport modelling  vehicle choice  social influence  technological learning  
Economic prospects and policy framework for hydrogen as fuel in the transport sector 期刊论文
ENERGY POLICY, 2018, 123: 280-288
作者:  Ajanovic, Amela;  Haas, Reinhard
收藏  |  浏览/下载:1/0  |  提交时间:2019/04/09
Electrolysis  Fuel cell vehicles  Economics  Technological learning  
Explaining technological change in the US wind industry: Energy policies, technological learning, and collaboration 期刊论文
ENERGY POLICY, 2018, 120: 197-212
作者:  Tang, Tian
收藏  |  浏览/下载:3/0  |  提交时间:2019/04/09
Technological change  Wind power  Learning curves  Renewable energy policies  Deregulation  Collaboration  
Competitiveness of advanced and conventional biofuels: Results from least-cost modelling of biofuel competition in Germany 期刊论文
ENERGY POLICY, 2017, 107
作者:  Millinger, M.;  Ponitka, J.;  Arendt, O.;  Thraen, D.
收藏  |  浏览/下载:3/0  |  提交时间:2019/04/09
Biofuels  Technological learning  Modelling  2nd generation  Advanced biofuels  Methane