M
Mikhail A. Pyatnitskiy
Researcher at Peninsular Malaysia
Publications - 50
Citations - 932
Mikhail A. Pyatnitskiy is an academic researcher from Peninsular Malaysia. The author has contributed to research in topics: Proteome & Shotgun proteomics. The author has an hindex of 14, co-authored 43 publications receiving 719 citations. Previous affiliations of Mikhail A. Pyatnitskiy include Russian Academy & Russian National Research Medical University.
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Journal ArticleDOI
The Size of the Human Proteome: The Width and Depth.
Elena A. Ponomarenko,Ekaterina V. Poverennaya,Ekaterina V. Ilgisonis,Mikhail A. Pyatnitskiy,Arthur T. Kopylov,Victor G. Zgoda,Andrey Lisitsa,Alexander I. Archakov +7 more
TL;DR: In this article, meta-analysis of neXtProt knowledge base is proposed for theoretical prediction of the number of different proteoforms that arise from alternative splicing (AS), single amino acid polymorphisms (SAPs), and posttranslational modifications (PTMs).
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Analysis of CRISPR system function in plant pathogen Xanthomonas oryzae.
Ekaterina Semenova,Maxim Nagornykh,Mikhail A. Pyatnitskiy,Irena I. Artamonova,Konstantin Severinov,Konstantin Severinov +5 more
TL;DR: This work determined CRISPR cassette sequences of two Xanthomonas oryzae strains and found that one of the strains remains sensitive to phage Xop411 despite carrying a cassette that has a spacer exactly matching a fragment of the Xop 411 genome.
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Extracting biological age from biomedical data via deep learning: too much of a good thing?
Timothy V. Pyrkov,Konstantin Slipensky,Mikhail Barg,Alexey Kondrashin,Boris Zhurov,Alexander Zenin,Mikhail A. Pyatnitskiy,L. I. Menshikov,Sergei Markov,Peter O. Fedichev +9 more
TL;DR: This work used one-week long physical activity records from a 2003–2006 National Health and Nutrition Examination Survey to compare three increasingly accurate biological age models and introduced a novel way to train parametric proportional hazards models suitable for out-of-the-box implementation with any modern machine learning software.
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Novel approach to meta-analysis of microarray datasets reveals muscle remodeling-related drug targets and biomarkers in Duchenne muscular dystrophy.
Ekaterina Kotelnikova,Maria Shkrob,Mikhail A. Pyatnitskiy,Alessandra Ferlini,Nikolai Daraselia +4 more
TL;DR: It is hypothesized that this process can affect the severity of DMD symptoms, making corresponding regulators and downstream genes valuable candidates for being potential drug targets and exploratory biomarkers.
Journal ArticleDOI
Human aqueous humor proteome in cataract, glaucoma, and pseudoexfoliation syndrome
Anna A. Kliuchnikova,Nadezhda I Samokhina,Irina Y. Ilina,Dmitry S. Karpov,Mikhail A. Pyatnitskiy,Ksenia G. Kuznetsova,Ilya Yu. Toropygin,Sergey A. Kochergin,Igor’ B Alekseev,Victor G. Zgoda,Alexander I. Archakov,Sergei A. Moshkovskii +11 more
TL;DR: Twenty‐nine human aqueous humor samples from patients with eye diseases such as cataract and glaucoma with and without pseudoexfoliation syndrome were characterized by LC–high resolution MS analysis, finding decrease in the level of apolipoprotein D as a marker of the pseudoexporiation syndrome.