Daniela Delneri

4.1k total citations
76 papers, 2.4k citations indexed

About

Daniela Delneri is a scholar working on Molecular Biology, Food Science and Plant Science. According to data from OpenAlex, Daniela Delneri has authored 76 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 26 papers in Food Science and 16 papers in Plant Science. Recurrent topics in Daniela Delneri's work include Fungal and yeast genetics research (41 papers), Fermentation and Sensory Analysis (26 papers) and Microbial Metabolic Engineering and Bioproduction (20 papers). Daniela Delneri is often cited by papers focused on Fungal and yeast genetics research (41 papers), Fermentation and Sensory Analysis (26 papers) and Microbial Metabolic Engineering and Bioproduction (20 papers). Daniela Delneri collaborates with scholars based in United Kingdom, Italy and United States. Daniela Delneri's co-authors include Stephen G. Oliver, Samina Naseeb, Edward J. Louis, Isabelle Colson, Marcin G. Fraczek, Ian N. Roberts, Richard J. Harrison, Sofia Grammenoudi, Simon C. Lovell and Csaba Pál and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Daniela Delneri

73 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniela Delneri United Kingdom 29 1.9k 632 617 299 231 76 2.4k
Karin Voordeckers Belgium 24 1.6k 0.8× 845 1.3× 604 1.0× 300 1.0× 302 1.3× 42 2.2k
Libuše Váchová Czechia 24 1.3k 0.7× 332 0.5× 319 0.5× 202 0.7× 206 0.9× 71 1.8k
Marı́a Molina Spain 31 2.6k 1.4× 360 0.6× 956 1.5× 249 0.8× 366 1.6× 97 3.4k
Joseph Schacherer France 27 1.9k 1.0× 920 1.5× 760 1.2× 458 1.5× 158 0.7× 89 2.4k
Zhi Li China 31 1.4k 0.8× 247 0.4× 1.8k 2.9× 189 0.6× 101 0.4× 127 2.9k
Charles S. Hoffman United States 32 4.4k 2.3× 333 0.5× 1.0k 1.6× 357 1.2× 487 2.1× 78 5.1k
Yang Dong China 24 1.3k 0.7× 124 0.2× 806 1.3× 194 0.6× 83 0.4× 106 2.1k
Juan Jiménez Spain 24 1.3k 0.7× 485 0.8× 420 0.7× 165 0.6× 132 0.6× 54 1.6k
Ana Cristina de Oliveira Monteiro‐Moreira Brazil 29 746 0.4× 222 0.4× 754 1.2× 124 0.4× 90 0.4× 91 2.1k
Kevin P. Byrne Ireland 21 2.0k 1.1× 533 0.8× 800 1.3× 414 1.4× 155 0.7× 57 2.5k

Countries citing papers authored by Daniela Delneri

Since Specialization
Citations

This map shows the geographic impact of Daniela Delneri's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniela Delneri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela Delneri more than expected).

Fields of papers citing papers by Daniela Delneri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela Delneri. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniela Delneri. The network helps show where Daniela Delneri may publish in the future.

Co-authorship network of co-authors of Daniela Delneri

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela Delneri. A scholar is included among the top collaborators of Daniela Delneri based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniela Delneri. Daniela Delneri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
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Latora, Vito, et al.. (2024). Minimisation of metabolic networks defines a new functional class of genes. Nature Communications. 15(1). 9076–9076.
3.
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Hollywood, Katherine A., et al.. (2024). Effect of Hanseniaspora vineae and Saccharomyces cerevisiae co-fermentations on aroma compound production in beer. Food Microbiology. 123. 104585–104585. 10 indexed citations
5.
Hu, Yue, et al.. (2024). Impact of inter-species hybridisation on antifungal drug response in the Saccharomyces genus. BMC Genomics. 25(1). 1165–1165. 1 indexed citations
6.
Bowyer, Paul, Andrew Currin, Daniela Delneri, & Marcin G. Fraczek. (2022). Telomere-to-telomere genome sequence of the model mould pathogen Aspergillus fumigatus. Nature Communications. 13(1). 5394–5394. 11 indexed citations
7.
Delneri, Daniela, et al.. (2022). Eisosome disruption by noncoding RNA deletion increases protein secretion in yeast. PNAS Nexus. 1(5). pgac241–pgac241. 2 indexed citations
8.
Hollywood, Katherine A., et al.. (2022). Volatile Aroma Compound Production Is Affected by Growth Rate in S. cerevisiae. Applied and Environmental Microbiology. 88(23). e0150922–e0150922. 3 indexed citations
9.
Hokamp, Karsten, et al.. (2022). Aneuploidy influences the gene expression profiles in Saccharomyces pastorianus group I and II strains during fermentation. PLoS Genetics. 18(4). e1010149–e1010149. 7 indexed citations
10.
Jones, Paul K., et al.. (2021). Biotechnological exploitation of Saccharomyces jurei and its hybrids in craft beer fermentation uncovers new aroma combinations. Food Microbiology. 100. 103838–103838. 26 indexed citations
11.
Naseeb, Samina, Yue Hu, Thomas Walsh, et al.. (2021). Restoring fertility in yeast hybrids: Breeding and quantitative genetics of beneficial traits. Proceedings of the National Academy of Sciences. 118(38). 26 indexed citations
12.
Parker, Steven J., Marcin G. Fraczek, Ping Wang, et al.. (2021). Functional and transcriptional profiling of non-coding RNAs in yeast reveal context-dependent phenotypes and in trans effects on the protein regulatory network. PLoS Genetics. 17(1). e1008761–e1008761. 18 indexed citations
13.
Delneri, Daniela, et al.. (2020). An update on the diversity, ecology and biogeography of the Saccharomyces genus. FEMS Yeast Research. 20(3). 46 indexed citations
14.
Hewitt, Sarah, et al.. (2020). Plasticity of Mitochondrial DNA Inheritance and Its Impact on Nuclear Gene Transcription in Yeast Hybrids. Microorganisms. 8(4). 494–494. 17 indexed citations
15.
Schwartz, Jean‐Marc, et al.. (2020). HybridMine: A Pipeline for Allele Inheritance and Gene Copy Number Prediction in Hybrid Genomes and Its Application to Industrial Yeasts. Microorganisms. 8(10). 1554–1554. 7 indexed citations
16.
Naseeb, Samina, et al.. (2018). Targeted metagenomics approach to capture the biodiversity of Saccharomyces genus in wild environments. Environmental Microbiology Reports. 11(2). 206–214. 21 indexed citations
17.
Parker, Steven J., Marcin G. Fraczek, Jian Wu, et al.. (2018). Large-scale profiling of noncoding RNA function in yeast. PLoS Genetics. 14(3). e1007253–e1007253. 28 indexed citations
18.
Parker, Steven J., Marcin G. Fraczek, Jian Wu, et al.. (2017). A resource for functional profiling of noncoding RNA in the yeast Saccharomyces cerevisiae. RNA. 23(8). 1166–1171. 10 indexed citations
19.
Naseeb, Samina, et al.. (2013). Chimeric Protein Complexes in Hybrid Species Generate Novel Phenotypes. PLoS Genetics. 9(10). e1003836–e1003836. 34 indexed citations
20.
Delneri, Daniela. (2011). Competition Experiments Coupled with High-Throughput Analyses for Functional Genomics Studies in Yeast. Methods in molecular biology. 759. 271–282. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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