Results 81 to 90 of about 9,193,993 (329)

Benchmark Evaluation of Protein–Protein Interaction Prediction Algorithms

Molecules, 2021
Protein–protein interactions (PPIs) perform various functions and regulate processes throughout cells. Knowledge of the full network of PPIs is vital to biomedical research, but most of the PPIs are still unknown.
Brandan Dunham, Madhavi K. Ganapathiraju
doaj   +1 more source

PTOMSM: A modified version of Topological Overlap Measure used for predicting Protein-Protein Interaction Network [PDF]

, 2009
A variety of methods are developed to integrating diverse biological data to predict novel interaction relationship between proteins. However, traditional integration can only generate protein interaction pairs within existing relationships.
Xun Huang
core   +2 more sources

Hematopoietic (stem) cells—The elixir of life?

FEBS Letters, EarlyView.
The aging of HSCs (hematopoietic stem cells) and the blood system leads to the decline of other organs. Rejuvenating aged HSCs improves the function of the blood system, slowing the aging of the heart, kidney, brain, and liver, and the occurrence of age‐related diseases.
Emilie L. Cerezo, Jonah Anderson, Emilie Dinh Vedrenne, Noël Yeh Martín, Jette Lengefeld   +4 more
wiley   +1 more source

Phosphatidylinositol 4‐kinase as a target of pathogens—friend or foe?

FEBS Letters, EarlyView.
This graphical summary illustrates the roles of phosphatidylinositol 4‐kinases (PI4Ks). PI4Ks regulate key cellular processes and can be hijacked by pathogens, such as viruses, bacteria and parasites, to support their intracellular replication. Their dual role as essential host enzymes and pathogen cofactors makes them promising drug targets.
Ana C. Mendes, Guilherme M. Azevedo, Amanda P. Barcellos, Diana Bahia   +3 more
wiley   +1 more source

Going the distance for protein function prediction: a new distance metric for protein interaction networks [PDF]

, 2013
Due to an error introduced in the production process, the x-axes in the first panels of Figure 1 and Figure 7 are not formatted correctly. The correct Figure 1 can be viewed here: http://dx.doi.org/10.1371/annotation/343bf260-f6ff-48a2-93b2 ...
Cao, Mengfei, Cowen, Lenore J., Crovella, Mark E., Daniels, Noah M., Hescott, Benjamin, Park, Jisoo, Zhang, Hao   +6 more
core   +4 more sources

Preferential attachment in the protein network evolution

, 2003
The Saccharomyces cerevisiae protein-protein interaction map, as well as many natural and man-made networks, shares the scale-free topology. The preferential attachment model was suggested as a generic network evolution model that yields this universal ...
A. Vazquez, B. K. Kay, C. von Mering, Eli Eisenberg, Erez Y. Levanon, H. Jeong, R. V. Sole, S. Ohno, S. B. Hedges   +8 more
core   +1 more source

Viruses.STRING: A Virus-Host Protein-Protein Interaction Database

bioRxiv, 2018
As viruses continue to pose risks to global health, having a better un-derstanding of virus–host protein–protein interactions aids in the development of treatments and vaccines.
H. Cook, Nadezhda Tsankova, Damian Szklarczyk, C. V. Mering, L. Jensen   +4 more
semanticscholar   +1 more source

Structural insights into lacto‐N‐biose I recognition by a family 32 carbohydrate‐binding module from Bifidobacterium bifidum

FEBS Letters, EarlyView.
Bifidobacterium bifidum establishes symbiosis with infants by metabolizing lacto‐N‐biose I (LNB) from human milk oligosaccharides (HMOs). The extracellular multidomain enzyme LnbB drives this process, releasing LNB via its catalytic glycoside hydrolase family 20 (GH20) lacto‐N‐biosidase domain.
Xinzhe Zhang, Naoki Sunagawa, Toma Kashima, Kiyohiko Igarashi, Akimasa Miyanaga, Shinya Fushinobu   +5 more
wiley   +1 more source

A cyclic peptide toolkit reveals mechanistic principles of peptidylarginine deiminase IV regulation

Nature Communications
Peptidylarginine deiminase IV (PADI4, PAD4) deregulation promotes the development of autoimmunity, cancer, atherosclerosis and age-related tissue fibrosis.
M. Teresa Bertran, Robert Walmsley, Thomas Cummings, Iker Valle Aramburu, Donald J. Benton, Rocio Mora Molina, Jayalini Assalaarachchi, Maria Chasampalioti, Tessa Swanton, Dhira Joshi, Stefania Federico, Hanneke Okkenhaug, Lu Yu, David Oxley, Simon Walker, Venizelos Papayannopoulos, Hiroaki Suga, Maria A. Christophorou, Louise J. Walport   +18 more
doaj   +1 more source

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions

BMC Bioinformatics, 2018
Background Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers.
Takanori Hayashi, Yuri Matsuzaki, Keisuke Yanagisawa, Masahito Ohue, Yutaka Akiyama   +4 more
doaj   +1 more source