Faculty Opinions recommendation of The bioplex network: A systematic exploration of the human interactome.

Author(s):  
Laura Trinkle-Mulcahy
Cell ◽  
2015 ◽  
Vol 162 (2) ◽  
pp. 425-440 ◽  
Author(s):  
Edward L. Huttlin ◽  
Lily Ting ◽  
Raphael J. Bruckner ◽  
Fana Gebreab ◽  
Melanie P. Gygi ◽  
...  

2020 ◽  
Author(s):  
Tsuyoshi Mita ◽  
Yu Harabuchi ◽  
Satoshi Maeda

The systematic exploration of synthetic pathways to afford a desired product through quantum chemical calculations remains a considerable challenge. In 2013, Maeda et al. introduced ‘quantum chemistry aided retrosynthetic analysis’ (QCaRA), which uses quantum chemical calculations to search systematically for decomposition paths of the target product and propose a synthesis method. However, until now, no new reactions suggested by QCaRA have been reported to lead to experimental discoveries. Using a difluoroglycine derivative as a target, this study investigated the ability of QCaRA to suggest various synthetic paths to the target without relying on previous data or the knowledge and experience of chemists. Furthermore, experimental verification of the seemingly most promising path led to the discovery of a synthesis method for the difluoroglycine derivative. The extent of the hands-on expertise of chemists required during the verification process was also evaluated. These insights are expected to advance the applicability of QCaRA to the discovery of viable experimental synthetic routes.


2020 ◽  
Author(s):  
Tsuyoshi Mita ◽  
Yu Harabuchi ◽  
Satoshi Maeda

The systematic exploration of synthetic pathways to afford a desired product through quantum chemical calculations remains a considerable challenge. In 2013, Maeda et al. introduced ‘quantum chemistry aided retrosynthetic analysis’ (QCaRA), which uses quantum chemical calculations to search systematically for decomposition paths of the target product and propose a synthesis method. However, until now, no new reactions suggested by QCaRA have been reported to lead to experimental discoveries. Using a difluoroglycine derivative as a target, this study investigated the ability of QCaRA to suggest various synthetic paths to the target without relying on previous data or the knowledge and experience of chemists. Furthermore, experimental verification of the seemingly most promising path led to the discovery of a synthesis method for the difluoroglycine derivative. The extent of the hands-on expertise of chemists required during the verification process was also evaluated. These insights are expected to advance the applicability of QCaRA to the discovery of viable experimental synthetic routes.


2019 ◽  
Vol 20 (3) ◽  
pp. 170-176 ◽  
Author(s):  
Zhongyan Li ◽  
Qingqing Miao ◽  
Fugang Yan ◽  
Yang Meng ◽  
Peng Zhou

Background:Protein–peptide recognition plays an essential role in the orchestration and regulation of cell signaling networks, which is estimated to be responsible for up to 40% of biological interaction events in the human interactome and has recently been recognized as a new and attractive druggable target for drug development and disease intervention.Methods:We present a systematic review on the application of machine learning techniques in the quantitative modeling and prediction of protein–peptide binding affinity, particularly focusing on its implications for therapeutic peptide design. We also briefly introduce the physical quantities used to characterize protein–peptide affinity and attempt to extend the content of generalized machine learning methods.Results:Existing issues and future perspective on the statistical modeling and regression prediction of protein– peptide binding affinity are discussed.Conclusion:There is still a long way to go before establishment of general, reliable and efficient machine leaningbased protein–peptide affinity predictors.


Fuel ◽  
2021 ◽  
Vol 287 ◽  
pp. 119434
Author(s):  
Jun Chen ◽  
Hongliang Li ◽  
Chunfu Liu ◽  
Lingyun Liu ◽  
Yu Sun ◽  
...  

2021 ◽  
Vol 2021 (8) ◽  
Author(s):  
Anamaría Font ◽  
Bernardo Fraiman ◽  
Mariana Graña ◽  
Carmen A. Núñez ◽  
Héctor Parra De Freitas

Abstract Compactifications of the heterotic string on special Td/ℤ2 orbifolds realize a landscape of string models with 16 supercharges and a gauge group on the left-moving sector of reduced rank d + 8. The momenta of untwisted and twisted states span a lattice known as the Mikhailov lattice II(d), which is not self-dual for d > 1. By using computer algorithms which exploit the properties of lattice embeddings, we perform a systematic exploration of the moduli space for d ≤ 2, and give a list of maximally enhanced points where the U(1)d+8 enhances to a rank d + 8 non-Abelian gauge group. For d = 1, these groups are simply-laced and simply-connected, and in fact can be obtained from the Dynkin diagram of E10. For d = 2 there are also symplectic and doubly-connected groups. For the latter we find the precise form of their fundamental groups from embeddings of lattices into the dual of II(2). Our results easily generalize to d > 2.


Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 675-682
Author(s):  
Victoria L Browning ◽  
Rebecca A Bergstrom ◽  
Sandra Daigle ◽  
John C Schimenti

Abstract Proper levels of gene expression are important for normal mammalian development. Typically, altered gene dosage caused by karyotypic abnormalities results in embryonic lethality or birth defects. Segmental aneuploidy can be compatible with life but often results in contiguous gene syndromes. The ability to manipulate the mouse genome allows the systematic exploration of regions that are affected by alterations in gene dosage. To explore the effects of segmental haploidy in the mouse t complex on chromosome 17, radiation-induced deletion complexes centered at the Sod2 and D17Leh94 loci were generated in embryonic stem (ES) cells. A small interval was identified that, when hemizygous, caused specific embryonic lethal phenotypes (exencephaly and edema) in most fetuses. The penetrance of these phenotypes was background dependent. Additionally, evidence for parent-of-origin effects was observed. This genetic approach should be useful for identifying genes that are imprinted or whose dosage is critical for normal embryonic development.


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