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Journal articles on the topic 'Protein association'

Author: Grafiati

Published: 6 September 2023

Last updated: 26 July 2025

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1

Grueninger, D., N. Treiber, M. O. P. Ziegler, J. W. A. Koetter, M. S. Schulze, and G. E. Schulz. "Designed Protein-Protein Association." Science 319, no. 5860 (2008): 206–9. http://dx.doi.org/10.1126/science.1150421.

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2

Pan, Albert C., Daniel Jacobson, Konstantin Yatsenko, Duluxan Sritharan, Thomas M. Weinreich, and David E. Shaw. "Atomic-level characterization of protein–protein association." Proceedings of the National Academy of Sciences 116, no. 10 (2019): 4244–49. http://dx.doi.org/10.1073/pnas.1815431116.

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Despite the biological importance of protein–protein complexes, determining their structures and association mechanisms remains an outstanding challenge. Here, we report the results of atomic-level simulations in which we observed five protein–protein pairs repeatedly associate to, and dissociate from, their experimentally determined native complexes using a molecular dynamics (MD)–based sampling approach that does not make use of any prior structural information about the complexes. To study association mechanisms, we performed additional, conventional MD simulations, in which we observed num

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3

Suratanee, Apichat, and Kitiporn Plaimas. "Heterogeneous Network Model to Identify Potential Associations Between Plasmodium vivax and Human Proteins." International Journal of Molecular Sciences 21, no. 4 (2020): 1310. http://dx.doi.org/10.3390/ijms21041310.

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Integration of multiple sources and data levels provides a great insight into the complex associations between human and malaria systems. In this study, a meta-analysis framework was developed based on a heterogeneous network model for integrating human-malaria protein similarities, a human protein interaction network, and a Plasmodium vivax protein interaction network. An iterative network propagation was performed on the heterogeneous network until we obtained stabilized weights. The association scores were calculated for qualifying a novel potential human-malaria protein association. This m

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4

Camacho, Carlos J., and Sandor Vajda. "Protein–protein association kinetics and protein docking." Current Opinion in Structural Biology 12, no. 1 (2002): 36–40. http://dx.doi.org/10.1016/s0959-440x(02)00286-5.

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5

Giles, K. "Interactions underlying subunit association in cholinesterases." Protein Engineering Design and Selection 10, no. 6 (1997): 677–85. http://dx.doi.org/10.1093/protein/10.6.677.

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6

Erickson, Harold P. "Co-operativity in protein-protein association." Journal of Molecular Biology 206, no. 3 (1989): 465–74. http://dx.doi.org/10.1016/0022-2836(89)90494-4.

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7

Lumry, R., and R. B. Gregory. "Dynamical factors in protein-protein association." Journal of Molecular Liquids 42 (October 1989): 113–44. http://dx.doi.org/10.1016/0167-7322(89)80029-7.

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8

Karplus, M., and J. Janin. "Comment on: `The entropy cost of protein association'." Protein Engineering, Design and Selection 12, no. 3 (1999): 185–86. http://dx.doi.org/10.1093/protein/12.3.185.

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9

Brandsdal, B. O., and A. O. Smalås. "Evaluation of protein–protein association energies by free energy perturbation calculations." Protein Engineering, Design and Selection 13, no. 4 (2000): 239–45. http://dx.doi.org/10.1093/protein/13.4.239.

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10

Zhou, Chun, Qimeng Wu, Ziliang Ye, et al. "Inverse Association Between Variety of Proteins With Appropriate Quantity From Different Food Sources and New-Onset Hypertension." Hypertension 79, no. 5 (2022): 1017–27. http://dx.doi.org/10.1161/hypertensionaha.121.18222.

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The relationships of the variety and quantity of different sources of dietary proteins with hypertension remain uncertain. We aimed to investigate associations between the variety and quantity of proteins intake from 8 major food sources and new-onset hypertension among 12 177 participants from the China Health and Nutrition Survey. Dietary intake was measured by 3 consecutive 24-hour dietary recalls combined with a household food inventory. The variety score of protein sources was defined as the number of protein sources consumed at the appropriate level, accounting for types and quantity of

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11

Zheng, W., N. P. Schafer, A. Davtyan, G. A. Papoian, and P. G. Wolynes. "Predictive energy landscapes for protein-protein association." Proceedings of the National Academy of Sciences 109, no. 47 (2012): 19244–49. http://dx.doi.org/10.1073/pnas.1216215109.

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12

Schreiber, G., G. Haran, and H. X. Zhou. "Fundamental Aspects of Protein−Protein Association Kinetics." Chemical Reviews 109, no. 3 (2009): 839–60. http://dx.doi.org/10.1021/cr800373w.

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13

Helms, Volkhard, Mazen Ahmad, Alexander Spaar, and Wei Gu. "Computer Simulation of Protein-Protein Association Processes." Biophysical Journal 96, no. 3 (2009): 75a. http://dx.doi.org/10.1016/j.bpj.2008.12.288.

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14

Pan, Albert C., Daniel Jacobson, Konstantin Borisov, Duluxan Sritharan, Thomas M. Weinreich, and David E. Shaw. "Atomic-Level Characterization of Protein-Protein Association." Biophysical Journal 114, no. 3 (2018): 557a. http://dx.doi.org/10.1016/j.bpj.2017.11.3045.

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15

Ramly, Balqis, Nor Afiqah-Aleng, and Zeti-Azura Mohamed-Hussein. "Protein–Protein Interaction Network Analysis Reveals Several Diseases Highly Associated with Polycystic Ovarian Syndrome." International Journal of Molecular Sciences 20, no. 12 (2019): 2959. http://dx.doi.org/10.3390/ijms20122959.

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Based on clinical observations, women with polycystic ovarian syndrome (PCOS) are prone to developing several other diseases, such as metabolic and cardiovascular diseases. However, the molecular association between PCOS and these diseases remains poorly understood. Recent studies showed that the information from protein–protein interaction (PPI) network analysis are useful in understanding the disease association in detail. This study utilized this approach to deepen the knowledge on the association between PCOS and other diseases. A PPI network for PCOS was constructed using PCOS-related pro

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16

Vlachy, Vojko, Yurij V. Kalyuzhnyi, Barbara Hribar-Lee, and Ken A. Dill. "Protein Association in Solution: Statistical Mechanical Modeling." Biomolecules 13, no. 12 (2023): 1703. http://dx.doi.org/10.3390/biom13121703.

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Protein molecules associate in solution, often in clusters beyond pairwise, leading to liquid phase separations and high viscosities. It is often impractical to study these multi-protein systems by atomistic computer simulations, particularly in multi-component solvents. Instead, their forces and states can be studied by liquid state statistical mechanics. However, past such approaches, such as the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, were limited to modeling proteins as spheres, and contained no microscopic structure–property relations. Recently, this limitation has been partly ove

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17

Goldman, Nick, Jeffrey L. Thorne, and David T. Jones. "Assessing the Impact of Secondary Structure and Solvent Accessibility on Protein Evolution." Genetics 149, no. 1 (1998): 445–58. http://dx.doi.org/10.1093/genetics/149.1.445.

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Abstract Empirically derived models of amino acid replacement are employed to study the association between various physical features of proteins and evolution. The strengths of these associations are statistically evaluated by applying the models of protein evolution to 11 diverse sets of protein sequences. Parametric bootstrap tests indicate that the solvent accessibility status of a site has a particularly strong association with the process of amino acid replacement that it experiences. Significant association between secondary structure environment and the amino acid replacement process i

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18

Dong, C., Y. Mahamat-Saleh, A. Racine, et al. "OP17 Protein intakes and risk of inflammatory bowel disease in the European Prospective Investigation into Cancer and Nutrition cohort (EPIC-IBD)." Journal of Crohn's and Colitis 14, Supplement_1 (2020): S015. http://dx.doi.org/10.1093/ecco-jcc/jjz203.016.

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Abstract Background Diet may contribute to inflammatory bowel disease (IBD) pathogenesis. In a previous French cohort, we found an association between high protein intake and increased risk of IBD. We aimed to investigate this relationship in the EPIC-IBD (European Prospective Investigation into Cancer and Nutrition – Inflammatory Bowel Diseases) cohort. Methods 413 593 participants from 8 European countries were included. Dietary data were collected at baseline from validated food frequency questionnaires. Mean daily intake of nutrients was assessed using the EPIC nutrient database. To reduce

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19

Betts, Matthew J., and Michael J. E. Sternberg. "An analysis of conformational changes on protein–protein association: implications for predictive docking." Protein Engineering, Design and Selection 12, no. 4 (1999): 271–83. http://dx.doi.org/10.1093/protein/12.4.271.

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20

G., S. Bhamra, K. Verma A., and B. Patel R. "AGENT ENABLED MINING OF DISTRIBUTED PROTEIN DATA BANKS." International Journal on Foundations of Computer Science & Technology (IJFCST) 5, no. 3 (2023): 21. https://doi.org/10.5281/zenodo.8279604.

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Mining biological data is an emergent area at the intersection between bioinformatics and data mining (DM). The intelligent agent based model is a popular approach in constructing Distributed Data Mining (DDM) systems to address scalable mining over large scale distributed data. The nature of associations between different amino acids in proteins has also been a subject of great anxiety. There is a strong need to develop new models and exploit and analyze the available distributed biological data sources. In this study, we have designed and implemented a multi-agent system (MAS) called Agent e

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21

Lee, Dong Heon, Chen Yao, Arunoday Bhan, et al. "Integrative Genomic Analysis Reveals Four Protein Biomarkers for Platelet Traits." Circulation Research 127, no. 9 (2020): 1182–94. http://dx.doi.org/10.1161/circresaha.119.316447.

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Rationale: Mean platelet volume (MPV) and platelet count (PLT) are platelet measures that have been linked to cardiovascular disease (CVD) and mortality risk. Identifying protein biomarkers for these measures may yield insights into CVD mechanisms. Objective: We aimed to identify causal protein biomarkers for MPV and PLT among 71 CVD-related plasma proteins measured in FHS (Framingham Heart Study) participants. Methods and Results: We conducted integrative analyses of genetic variants associated with PLT/MPV with protein quantitative trait locus variants associated with plasma proteins followe

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22

Toshiko, Tanaka, Jayanta Das, Qu Tian, et al. "PLANT PROTEIN BUT NOT ANIMAL PROTEIN CONSUMPTION IS ASSOCIATED WITH FRAILTY THROUGH PLASMA METABOLITES." Innovation in Aging 7, Supplement_1 (2023): 1098–99. http://dx.doi.org/10.1093/geroni/igad104.3528.

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Abstract There is evidence that the association of protein intake and frailty may depend on the source of dietary protein. The mechanism underlying these associations are not clear. In this study, we explore circulating metabolites as mediators of the relationship between dietary protein and of frailty in participants of the Baltimore Longitudinal Study of Aging (BLSA). Cross-sectional analyses in 735 BLSA participants of associations between plant and animal protein intake and frailty. Usual protein intake from plant and animal sources were estimated with a Food Frequency Questionnaire (FFQ)

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23

Brems, David N., Leila A. Alter, Michael J. Beckage, et al. "Altering the association properties of insulin by amino acid replacement." "Protein Engineering, Design and Selection" 5, no. 6 (1992): 527–33. http://dx.doi.org/10.1093/protein/5.6.527.

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24

Hope, John N., Hao-Chia Chen та J. Fidding Hejtmancik. "βA3/Al-crystallin association: role of the N-terminal arm". "Protein Engineering, Design and Selection" 7, № 3 (1994): 445–51. http://dx.doi.org/10.1093/protein/7.3.445.

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25

Bethea, Deidra, Sheng-Jiun Wu, Jinquan Luo, et al. "Mechanisms of self-association of a human monoclonal antibody CNTO607." Protein Engineering, Design and Selection 25, no. 10 (2012): 531–38. http://dx.doi.org/10.1093/protein/gzs047.

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26

Rajagopal, Nandhini, and Shikha Nangia. "Obtaining Protein Association Energy Landscape for Integral Membrane Proteins." Journal of Chemical Theory and Computation 15, no. 11 (2019): 6444–55. http://dx.doi.org/10.1021/acs.jctc.9b00626.

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27

Gabdoulline, Razif R., and Rebecca C. Wade. "Protein-protein association: investigation of factors influencing association rates by Brownian dynamics simulations." Journal of Molecular Biology 306, no. 5 (2001): 1139–55. http://dx.doi.org/10.1006/jmbi.2000.4404.

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28

Dimitrova, Maria, Isabelle Imbert, Marie Paule Kieny, and Catherine Schuster. "Protein-Protein Interactions between Hepatitis C Virus Nonstructural Proteins." Journal of Virology 77, no. 9 (2003): 5401–14. http://dx.doi.org/10.1128/jvi.77.9.5401-5414.2003.

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ABSTRACT Replication of the hepatitis C virus (HCV) genome has been proposed to take place close to the membrane of the endoplasmic reticulum in membrane-associated replicase complexes, as is the case with several other plus-strand RNA viruses, such as poliovirus and flaviviruses. The most obvious benefits of this property are the possibility of coupling functions residing in different polypeptidic chains and the sequestration of viral proteins and nucleic acids in a distinct cytoplasmic compartment with high local concentrations of viral components. Indeed, HCV nonstructural (NS) proteins wer

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29

Kendellen, Megan F., Katharine S. Barrientos, and Christopher M. Counter. "POT1 Association with TRF2 Regulates Telomere Length." Molecular and Cellular Biology 29, no. 20 (2009): 5611–19. http://dx.doi.org/10.1128/mcb.00286-09.

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ABSTRACT Deleting the OB folds encoding the telomeric single-stranded DNA (ssDNA)-binding activity of the human telomeric protein POT1 induces significant telomere elongation, suggesting that at least one critical aspect of the regulation of telomere length is disrupted by this POT1ΔOB mutant protein. POT1 is known to associate with two proteins through the protein interaction domain retained in POT1ΔOB—the telomeric double-stranded DNA-binding protein TRF2 and the telomere-associated protein TPP1. We report that introducing a mutation that reduces association of POT1 with TRF2, but not a muta

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30

Tanaka, Toshiko, Jayanta K. Das, Yichen Jin, et al. "Plant Protein but Not Animal Protein Consumption Is Associated with Frailty through Plasma Metabolites." Nutrients 15, no. 19 (2023): 4193. http://dx.doi.org/10.3390/nu15194193.

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There is evidence that the association of protein intake and frailty may depend on the source of dietary protein. The mechanism underlying this association is not clear. In this study, we explore circulating metabolites as mediators of the relationship between dietary protein and of frailty in participants of the Baltimore Longitudinal Study of Aging (BLSA). Cross-sectional analyses in 735 BLSA participants of associations between plant and animal protein intake and frailty. Usual protein intake from plant and animal sources were estimated with a Food Frequency Questionnaire (FFQ) and frailty

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31

Szczepaniak, Andrzej, Karin Frank, and Jacek Rybka. "Membrane Association of the Rieske Iron-Sulfur Protein." Zeitschrift für Naturforschung C 50, no. 7-8 (1995): 535–42. http://dx.doi.org/10.1515/znc-1995-7-811.

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Abstract The mode of membrane attachment of the Rieske iron -sulfur proteins from cytochrome b6ƒ complex of pea thylakoids and from cytochrome bc1 complex of yeast mitochondria has been studied using biochemical approaches. The relative sensitivity of the Rieske protein to trypsin in the thylakoid membrane shows that all trypsin sites of the Rieske protein are on the lumen side of the thylakoid membrane. In contrast to cytochrome / the chloroplast Rieske protein was extracted from thylakoids using chaotropic agents (NaSCN, urea), an alkaline pH and relatively low concentrations of Trinon X-100

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32

Ben-Naim, Arieh. "On the driving forces for protein-protein association." Journal of Chemical Physics 125, no. 2 (2006): 024901. http://dx.doi.org/10.1063/1.2205860.

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33

Qin, Sanbo, and Huan-Xiang Zhou. "Automated Prediction of Protein-Protein Association Rate Constants." Biophysical Journal 100, no. 3 (2011): 386a. http://dx.doi.org/10.1016/j.bpj.2010.12.2295.

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34

Kovalenko, I. B., A. M. Abaturova, A. N. Diakonova, et al. "Computer Simulation of Protein-Protein Association in Photosynthesis." Mathematical Modelling of Natural Phenomena 6, no. 7 (2011): 39–54. http://dx.doi.org/10.1051/mmnp/20116704.

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35

Gilmore, Jason M., Deanna L. Auberry, Julia L. Sharp, Amanda M. White, Kevin K. Anderson, and Don S. Daly. "A Bayesian estimator of protein–protein association probabilities." Bioinformatics 24, no. 13 (2008): 1554–55. http://dx.doi.org/10.1093/bioinformatics/btn238.

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36

Elefsinioti, Antigoni, Ömer Sinan Saraç, Anna Hegele, et al. "Large-scaleDe NovoPrediction of Physical Protein-Protein Association." Molecular & Cellular Proteomics 10, no. 11 (2011): M111.010629. http://dx.doi.org/10.1074/mcp.m111.010629.

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37

Ben-Naim, A. "Solvent effects on protein association and protein folding." Biopolymers 29, no. 3 (1990): 567–96. http://dx.doi.org/10.1002/bip.360290312.

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38

Ruvinsky, Anatoly M., Tatsiana Kirys, Alexander V. Tuzikov, and Ilya A. Vakser. "Side-Chain Conformational Changes upon Protein–Protein Association." Journal of Molecular Biology 408, no. 2 (2011): 356–65. http://dx.doi.org/10.1016/j.jmb.2011.02.030.

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39

Sebastiani, Paola, Anastasia Gurinovich, Zeyuan Song, et al. "Effect of Longevity Genetic Variants on the Molecular Aging Rate." Innovation in Aging 4, Supplement_1 (2020): 852. http://dx.doi.org/10.1093/geroni/igaa057.3130.

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Abstract We conducted a genome-wide association study of 1317 centenarians from the New England Centenarian Study and 2885 controls using &gt;9M genetic variants. The most significantly associated variants were correlated to 4131 serum proteins in 224 study participants. The genetic and protein associations were replicated in a genome-wide association study of 480 centenarians and ~800 controls of Ashkenazy Jewish descent and a proteomic scan of approximately 1000 participants of the same study. The analysis replicated a protein signature associated with APOE genotypes and confirmed strong

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40

Coelho-Júnior, Hélio José, Riccardo Calvani, Francesco Landi, Anna Picca, and Emanuele Marzetti. "Protein Intake and Cognitive Function in Older Adults: A Systematic Review and Meta-Analysis." Nutrition and Metabolic Insights 14 (January 2021): 117863882110223. http://dx.doi.org/10.1177/11786388211022373.

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Introduction: The present study investigated the association between protein intake and cognitive function in older adults. Methods: We performed a literature search with no restriction on publication year in MEDLINE, SCOPUS, CINAHL, AgeLine from inception up to October 2020. Observational studies that investigated as a primary or secondary outcome the association of protein intake and cognitive function in older adults aged ⩾60 years were included. Results: Nine cross-sectional studies that investigated a total of 4929 older adults were included in the qualitative analysis. Overall cognitive

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41

Prat-Gay, Gonzalo de. "Association of complementary fragments and the elucidation of protein folding pathways." "Protein Engineering, Design and Selection" 9, no. 10 (1996): 843–47. http://dx.doi.org/10.1093/protein/9.10.843.

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42

Hejtmancik, J. F., P. T. Wingfield, C. Chambers, et al. "Association properties of betaB2- and betaA3-crystallin: ability to form dimers." Protein Engineering Design and Selection 10, no. 11 (1997): 1347–52. http://dx.doi.org/10.1093/protein/10.11.1347.

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43

Dhusia, Kalyani, Zhaoqian Su, and Yinghao Wu. "Using Coarse-Grained Simulations to Characterize the Mechanisms of Protein–Protein Association." Biomolecules 10, no. 7 (2020): 1056. http://dx.doi.org/10.3390/biom10071056.

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The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein–protein association. We systematically calibrated our simulation

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44

Chasman, D. I., and R. D. Kornberg. "GAL4 protein: purification, association with GAL80 protein, and conserved domain structure." Molecular and Cellular Biology 10, no. 6 (1990): 2916–23. http://dx.doi.org/10.1128/mcb.10.6.2916-2923.1990.

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Expression of the yeast Saccharomyces cerevisiae GAL4 protein under its own (galactose-inducible) control gave 5 to 10 times the level of protein observed when the GAL4 gene was on a high-copy plasmid. Purification of GAL4 by a procedure including affinity chromatography on a GAL4-binding DNA column yielded not only GAL4 but also a second protein, shown to be GAL80 by its reaction with an antipeptide antibody. Sequence comparisons of GAL4 and other members of a family of proteins sharing homologous cysteine finger motifs identified an additional region of homology in the middle of these protei

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45

Chasman, D. I., and R. D. Kornberg. "GAL4 protein: purification, association with GAL80 protein, and conserved domain structure." Molecular and Cellular Biology 10, no. 6 (1990): 2916–23. http://dx.doi.org/10.1128/mcb.10.6.2916.

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Expression of the yeast Saccharomyces cerevisiae GAL4 protein under its own (galactose-inducible) control gave 5 to 10 times the level of protein observed when the GAL4 gene was on a high-copy plasmid. Purification of GAL4 by a procedure including affinity chromatography on a GAL4-binding DNA column yielded not only GAL4 but also a second protein, shown to be GAL80 by its reaction with an antipeptide antibody. Sequence comparisons of GAL4 and other members of a family of proteins sharing homologous cysteine finger motifs identified an additional region of homology in the middle of these protei

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46

Kabli, Fatima, Reda Mohamed Hamou, and Abdelmalek Amine. "Protein Classification Using N-gram Technique and Association Rules." International Journal of Software Innovation 6, no. 2 (2018): 77–89. http://dx.doi.org/10.4018/ijsi.2018040106.

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The knowledge extraction process from biological data is increasingly being considered, it addresses general issues such as grouping, classification and association; The Protein classification is an important activity for the biologist to respond to biological needs. For this reason, the authors present a global framework inspired by the knowledge extraction process from biological data to classified proteins from their primary structure based on the association rules. This framework has three main steps: The first one is, the pre-processing phase, consists of extracting descriptors by N-Gram

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47

Kumari, Bandana, Ravindra Kumar, and Manish Kumar. "Identifying residues that determine palmitoylation using association rule mining." Bioinformatics 35, no. 17 (2019): 2887–90. http://dx.doi.org/10.1093/bioinformatics/btz003.

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Abstract Motivation In eukaryotes, palmitoylation drives several essential cellular mechanisms like protein sorting, protein stability and protein–protein interaction. Several amino acids namely Cys, Gly, Ser, Thr and Lys undergo palmitoylation. But very little is known about the amino acid patterns that promote palmitoylation. Results We deduced presence of statistically significant amino acids around palmitoylation sites and their association with different palmitoylated residues i.e. Cys, Gly and Ser. The results suggest that palmitoylation, irrespective of its target residue, generally occ

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48

Sahu, Surasri Nandan, Mohammed Abdul Khadeer, Brian W. Robertson, Stephanie M. Núñez, Guang Bai, and Anandarup Gupta. "Association of leupaxin with Src in osteoclasts." American Journal of Physiology-Cell Physiology 292, no. 1 (2007): C581—C590. http://dx.doi.org/10.1152/ajpcell.00636.2005.

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Leupaxin (LPXN), which belongs to the paxillin extended family of adaptor proteins, was previously identified as a component of the sealing zone in osteoclasts. LPXN was found to associate with several podosomal proteins, such as the protein tyrosine kinase Pyk2, the protein-tyrosine phosphatase-PEST (PTP-PEST), actin-binding proteins, and regulators of actin cytoskeletal reorganization. It was previously demonstrated that inhibition of LPXN expression resulted in reduced osteoclast-mediated resorption. In the current study, overexpression of LPXN in murine osteoclasts resulted in both enhance

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49

Ziaunys, Mantas, Kamile Mikalauskaite, Lukas Krasauskas, and Vytautas Smirnovas. "Conformation-Specific Association of Prion Protein Amyloid Aggregates with Tau Protein Monomers." International Journal of Molecular Sciences 24, no. 11 (2023): 9277. http://dx.doi.org/10.3390/ijms24119277.

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Protein aggregation into amyloid fibrils is associated with several amyloidoses, including neurodegenerative Alzheimer’s and Parkinson’s diseases. Despite years of research and numerous studies, the process is still not fully understood, which significantly impedes the search for cures of amyloid-related disorders. Recently, there has been an increase in reports of amyloidogenic protein cross-interactions during the fibril formation process, which further complicates the already intricate process of amyloid aggregation. One of these reports displayed an interaction involving Tau and prion prot

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50

Mayer, Melanie L., and Philip Hieter. "Protein networks—built by association." Nature Biotechnology 18, no. 12 (2000): 1242–43. http://dx.doi.org/10.1038/82342.

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