Python按关键字提取txt文本并保存到Excel
从web of science导出了许多（200多）篇文章的相关信息，如标题、摘要、关键字、作者、参考文献、起始页码，发表的期刊等等信息，不同文章之间通过空行隔开。下面我放了两篇文章的信息，对每一篇文章来说，我只想要提取其中的部分信息，将它写成一个excel表格，关键在于如何对数据进行分割？
PT J
AU Newman, JRS
Ghaemmaghami, S
Ihmels, J
Breslow, DK
Noble, M
DeRisi, JL
Weissman, JS
AF Newman, John R. S.
Ghaemmaghami, Sina
Ihmels, Jan
Breslow, David K.
Noble, Matthew
DeRisi, Joseph L.
Weissman, Jonathan S.
TI Single-cell proteomic analysis of S-cerevisiae reveals the architecture
of biological noise
SO NATURE
LA English
DT Article
ID STOCHASTIC GENE-EXPRESSION; MESSENGER-RNA; FLUORESCENT PROTEIN;
EUKARYOTIC GENOME; GLOBAL ANALYSIS; YEAST PROTEOME; SYSTEM;
LOCALIZATION; DYNAMICS; SWITCH
AB A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.
C1 Univ Calif San Francisco, Howard Hughes Med Inst, San Francisco, CA 94107 USA.
Univ Calif San Francisco, Dept Cellular & Mol Pharmacol, San Francisco, CA 94107 USA.
Univ Calif San Francisco, Dept Biochem & Biophys, San Francisco, CA 94107 USA.
Calif Inst Quantitat Biomed Res, San Francisco, CA 94107 USA.
RP Newman, JRS (通讯作者)，Univ Calif San Francisco, Howard Hughes Med Inst, 1700 4th St, San Francisco, CA 94107 USA.
EM weissman@cmp.ucsf.edu
OI Ghaemmaghami, Sina/0000-0002-8696-2950; Breslow,
David/0000-0003-0245-3348
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NR 45
TC 1093
Z9 1103
U1 3
U2 220
PU NATURE PUBLISHING GROUP
PI LONDON
PA MACMILLAN BUILDING, 4 CRINAN ST, LONDON N1 9XW, ENGLAND
SN 0028-0836
EI 1476-4687
J9 NATURE
JI Nature
PD JUN 15
PY 2006
VL 441
IS 7095
BP 840
EP 846
DI 10.1038/nature04785
PG 7
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 052SL
UT WOS:000238254100035
PM 16699522
DA 2022-05-02
ER
PT J
AU Thattai, M
van Oudenaarden, A
AF Thattai, M
van Oudenaarden, A
TI Intrinsic noise in gene regulatory networks
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
AMERICA
LA English
DT Article
ID ESCHERICHIA-COLI; TRANSCRIPTION INITIATION; EXPRESSION; FLUCTUATIONS;
TRANSLATION; PROMOTER; MODEL; REPRESSOR; LAMBDA
AB Cells are intrinsically noisy biochemical reactors: low reactant numbers can lead to significant statistical fluctuations in molecule numbers and reaction rates. Here we use an analytic model to investigate the emergent noise properties of genetic systems. We find for a single gene that noise is essentially determined at the translational level, and that the mean and variance of protein concentration can be independently controlled. The noise strength immediately following single gene induction is almost twice the final steady-state value, We find that fluctuations in the concentrations of a regulatory protein can propagate through a genetic cascade; translational noise control could explain the inefficient translation rates observed for genes encoding such regulatory proteins, For an autoregulatory protein, we demonstrate that negative feedback efficiently decreases system noise. The model can be used to predict the noise characteristics of networks of arbitrary connectivity. The general procedure is further illustrated for an autocatalytic protein and a bistable genetic switch, The analysis of intrinsic noise reveals biological roles of gene network structures and can lead to a deeper understanding of their evolutionary origin.
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RP van Oudenaarden, A (通讯作者)，MIT, Dept Phys, Room 13-2010,77 Massachusetts Ave, Cambridge, MA 02139 USA.
EM avano@mit.edu
RI van Oudenaarden, Alexander/AAA-1705-2019
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NR 29
TC 1022
Z9 1033
U1 4
U2 72
PU NATL ACAD SCIENCES
PI WASHINGTON
PA 2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA
SN 0027-8424
J9 P NATL ACAD SCI USA
JI Proc. Natl. Acad. Sci. U. S. A.
PD JUL 17
PY 2001
VL 98
IS 15
BP 8614
EP 8619
DI 10.1073/pnas.151588598
PG 6
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics
GA 454HK
UT WOS:000169967000074
PM 11438714
OA Bronze, Green Published
DA 2022-05-02
ER
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