Andrey Grigoriev

Prof. Andrey Grigoriev

Department of Biology, Center for Computational and Integrative Biology, Rutgers University, Camden, NJ 08102, USA
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Research Focus & Metrics

Academic Career Length

37Years (1990-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 May 1998 in Nucleic Acids Research
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Andrey GrigorievAndrey Grigoriev
Andrey Grigoriev
A novel method of cumulative diagrams shows that the nucleotide composition of a microbial chromosome changes at two points separated by about a half of its length. These points coincide with sites of replication origin and terminus for all bacteria where such sites are known. The leading strand is found to contain more guanine than cytosine residues. This fact is used to predict origin and terminus locations in other bacterial and archaeal genomes. Local changes, visible as diagram distortions, may represent recent genome rearrangements, as demonstrated for two strains of Escherichia coli. Analysis of the diagrams of viral and mitochondrial genomes suggests a link between the base composition bias and the time spent by DNA in a single stranded state during replication.

1 September 2001 in Nucleic Acids Research
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Andrey GrigorievAndrey Grigoriev
Andrey Grigoriev
The relationship between the similarity of expression patterns for a pair of genes and interaction of the proteins they encode is demonstrated both for the simple genome of the bacteriophage T7 and the considerably more complex genome of the yeast Saccharomyces cerevisiae. Statistical analysis of large-scale gene expression and protein interaction data shows that protein pairs encoded by co-expressed genes interact with each other more frequently than with random proteins. Furthermore, the mean similarity of expression profiles is significantly higher for respective interacting protein pairs than for random ones. Such coupled analysis of gene expression and protein interaction data may allow evaluation of the results of large-scale gene expression and protein interaction screens as demonstrated for several publicly available datasets. The role of this link between expression and interaction in the evolution from monomeric to oligomeric protein structures is also discussed.

16 April 2019 in Genome Research
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RFRoven Rommel Fuentes
Roven Rommel Fuentes
DCDmytro Chebotarov
Dmytro Chebotarov
JDJorge Duitama
Jorge Duitama
SSSean Smith
Sean Smith
JHJuan Fernando De la Hoz
Juan Fernando De la Hoz
NANickolai Alexandrov
Nickolai Alexandrov
Investigation of large structural variants (SVs) is a challenging yet important task in understanding trait differences in highly repetitive genomes. Combining different bioinformatic approaches for SV detection, we analyzed whole-genome sequencing data from 3000 rice genomes and identified 63 million individual SV calls that grouped into 1.5 million allelic variants. We found enrichment of long SVs in promoters and an excess of shorter variants in 5′ UTRs. Across the rice genomes, we identified regions of high SV frequency enriched in stress response genes. We demonstrated how SVs may help in finding causative variants in genome-wide association analysis. These new insights into rice genome biology are valuable for understanding the effects SVs have on gene function, with the prospect of identifying novel agronomically important alleles that can be utilized to improve cultivated rice.

15 July 2003 in Nucleic Acids Research
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Andrey GrigorievAndrey Grigoriev
Andrey Grigoriev
F1000Prime Recommended Article: On the number of protein-protein interactions in the yeast proteome.


16 September 2015 in Biology Direct
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SKSpyros Karaiskos
Spyros Karaiskos
ANAmmar S. Naqvi
Ammar S. Naqvi
KSKarl E. Swanson
Karl E. Swanson
Andrey GrigorievAndrey Grigoriev
Andrey Grigoriev
Development of sequencing technologies and supporting computation enable discovery of small RNA molecules that previously escaped detection or were ignored due to low count numbers. While the focus in the analysis of small RNA libraries has been primarily on microRNAs (miRNAs), recent studies have reported findings of fragments of transfer RNAs (tRFs) across a range of organisms. Here we describe Drosophila melanogaster tRFs, which appear to have a number of structural and functional features similar to those of miRNAs but are less abundant. As is the case with miRNAs, (i) tRFs seem to have distinct isoforms preferentially originating from 5’ or 3’ end of a precursor molecule (in this case, tRNA), (ii) ends of tRFs appear to contain short “seed” sequences matching conserved regions across 12 Drosophila genomes, preferentially in 3’ UTRs but also in introns and exons; (iii) tRFs display specific isoform loading into Ago1 and Ago2 and thus likely function in RISC complexes; (iii) levels of loading in Ago1 and Ago2 differ considerably; and (iv) both tRF expression and loading appear to be age-dependent, indicating potential regulatory changes from young to adult organisms. We found that Drosophila tRF reads mapped to both nuclear and mitochondrial tRNA genes for all 20 amino acids, while previous studies have usually reported fragments from only a few tRNAs. These tRFs show a number of similarities with miRNAs, including seed sequences. Based on complementarity with conserved Drosophila regions we identified such seed sequences and their possible targets with matches in the 3’UTR regions. Strikingly, the potential target genes of the most abundant tRFs show significant Gene Ontology enrichment in development and neuronal function. The latter suggests that involvement of tRFs in the RNA interfering pathway may play a role in brain activity or brain changes with age. This article was reviewed by Eugene Koonin, Neil Smalheiser and Alexander Kel.