Emanuel Weitschek

1.5k total citations
37 papers, 1.0k citations indexed

About

Emanuel Weitschek is a scholar working on Molecular Biology, Artificial Intelligence and Ecology. According to data from OpenAlex, Emanuel Weitschek has authored 37 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 8 papers in Artificial Intelligence and 5 papers in Ecology. Recurrent topics in Emanuel Weitschek's work include Genomics and Phylogenetic Studies (13 papers), Gene expression and cancer classification (11 papers) and Machine Learning in Bioinformatics (6 papers). Emanuel Weitschek is often cited by papers focused on Genomics and Phylogenetic Studies (13 papers), Gene expression and cancer classification (11 papers) and Machine Learning in Bioinformatics (6 papers). Emanuel Weitschek collaborates with scholars based in Italy, United States and Russia. Emanuel Weitschek's co-authors include Giovanni Felici, Paola Bertolazzi, Giulia Fiscon, Robin van Velzen, Freek T. Bakker, Maria Cristina De Cola, Simona De Salvo, Fabio Cumbo, Placido Bramanti and Alessia Bramanti and has published in prestigious journals such as Bioinformatics, PLoS ONE and European Journal of Operational Research.

In The Last Decade

Emanuel Weitschek

35 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emanuel Weitschek Italy 16 544 200 150 136 114 37 1.0k
Giovanni Felici Italy 20 599 1.1× 153 0.8× 205 1.4× 148 1.1× 122 1.1× 75 1.3k
Paola Bertolazzi Italy 17 404 0.7× 155 0.8× 152 1.0× 67 0.5× 49 0.4× 54 981
Thomas Lingner Germany 25 1.1k 2.0× 371 1.9× 67 0.4× 82 0.6× 136 1.2× 49 2.0k
Kyungsook Han South Korea 25 1.5k 2.7× 33 0.2× 130 0.9× 94 0.7× 97 0.9× 100 1.8k
Arjun Krishnan United States 20 1.8k 3.4× 150 0.8× 50 0.3× 531 3.9× 36 0.3× 47 3.3k
Faraz Faghri United States 15 810 1.5× 38 0.2× 284 1.9× 182 1.3× 48 0.4× 27 1.8k
Uğis Sarkans United Kingdom 18 1.9k 3.4× 106 0.5× 96 0.6× 254 1.9× 48 0.4× 29 2.5k
C. Arenas Spain 15 181 0.3× 60 0.3× 58 0.4× 274 2.0× 95 0.8× 65 720
Adi Maron‐Katz Israel 15 515 0.9× 380 1.9× 69 0.5× 53 0.4× 10 0.1× 21 1.2k
Daifeng Wang United States 18 585 1.1× 51 0.3× 63 0.4× 173 1.3× 38 0.3× 58 945

Countries citing papers authored by Emanuel Weitschek

Since Specialization
Citations

This map shows the geographic impact of Emanuel Weitschek'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 Emanuel Weitschek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emanuel Weitschek more than expected).

Fields of papers citing papers by Emanuel Weitschek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Emanuel Weitschek. 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 Emanuel Weitschek. The network helps show where Emanuel Weitschek may publish in the future.

Co-authorship network of co-authors of Emanuel Weitschek

This figure shows the co-authorship network connecting the top 25 collaborators of Emanuel Weitschek. A scholar is included among the top collaborators of Emanuel Weitschek 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 Emanuel Weitschek. Emanuel Weitschek 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.
2.
Cumbo, Fabio, Emanuel Weitschek, & Daniel Blankenberg. (2023). hdlib: A Python library for designing Vector-SymbolicArchitectures. The Journal of Open Source Software. 8(89). 5704–5704. 2 indexed citations
3.
Weitschek, Emanuel, et al.. (2021). Price Discrimination in the Online Airline Market: An Empirical Study. Journal of theoretical and applied electronic commerce research. 16(6). 2282–2303. 13 indexed citations
4.
Felici, Giovanni, et al.. (2018). Combining DNA methylation and RNA sequencing data of cancer for supervised knowledge extraction. BioData Mining. 11(1). 22–22. 20 indexed citations
5.
Fiscon, Giulia, Emanuel Weitschek, Giovanni Felici, et al.. (2018). Combining EEG signal processing with supervised methods for Alzheimer’s patients classification. BMC Medical Informatics and Decision Making. 18(1). 35–35. 118 indexed citations
6.
Weitschek, Emanuel, et al.. (2018). CamurWeb: a classification software and a large knowledge base for gene expression data of cancer. BMC Bioinformatics. 19(S10). 354–354. 9 indexed citations
7.
Cumbo, Fabio, Giulia Fiscon, Stefano Ceri, Marco Masseroli, & Emanuel Weitschek. (2017). TCGA2BED: extracting, extending, integrating, and querying The Cancer Genome Atlas. BMC Bioinformatics. 18(1). 6–6. 22 indexed citations
8.
Bertolazzi, Paola, et al.. (2017). A novel method and software for automatically classifying Alzheimer’s disease patients by magnetic resonance imaging analysis. Computer Methods and Programs in Biomedicine. 143. 89–95. 31 indexed citations
9.
Fiscon, Giulia, Emanuel Weitschek, Eleonora Cella, et al.. (2016). MISSEL: a method to identify a large number of small species-specific genomic subsequences and its application to viruses classification. BioData Mining. 9(1). 38–38. 11 indexed citations
10.
Weitschek, Emanuel, Daniele Santoni, Giulia Fiscon, et al.. (2014). Next generation sequencing reads comparison with an alignment-free distance. BMC Research Notes. 7(1). 869–869. 9 indexed citations
11.
Weitschek, Emanuel, Giulia Fiscon, & Giovanni Felici. (2014). Supervised DNA Barcodes species classification: analysis, comparisons and results. BioData Mining. 7(1). 4–4. 73 indexed citations
12.
Polychronopoulos, Dimitris, Emanuel Weitschek, Slavica Dimitrieva, et al.. (2014). Classification of selectively constrained DNA elements using feature vectors and rule-based classifiers. Genomics. 104(2). 79–86. 21 indexed citations
13.
Weitschek, Emanuel, Giovanni Felici, & Paola Bertolazzi. (2013). Clinical Data Mining: Problems, Pitfalls and Solutions. 90–94. 16 indexed citations
14.
Felici, Giovanni & Emanuel Weitschek. (2012). Mining logic models in the presence of noisy data.. 2 indexed citations
15.
Weitschek, Emanuel, Giovanni Felici, & Paola Bertolazzi. (2012). MALA: A Microarray Clustering and Classification Software. 6. 201–205. 14 indexed citations
16.
Velzen, Robin van, Emanuel Weitschek, Giovanni Felici, & Freek T. Bakker. (2012). DNA Barcoding of Recently Diverged Species: Relative Performance of Matching Methods. PLoS ONE. 7(1). e30490–e30490. 144 indexed citations
17.
Weitschek, Emanuel, Alessandra Lo Presti, Giovanni Felici, et al.. (2012). Human polyomaviruses identification by logic mining techniques. Virology Journal. 9(1). 58–58. 13 indexed citations
18.
Weitschek, Emanuel, Robin van Velzen, & Giovanni Felici. (2011). Species classification using DNA Barcode sequences: A comparative analysis. Socio-Environmental Systems Modeling. 4 indexed citations
19.
Arisi, Ivan, Mara D’Onofrio, Rossella Brandi, et al.. (2011). Gene Expression Biomarkers in the Brain of a Mouse Model for Alzheimer's Disease: Mining of Microarray Data by Logic Classification and Feature Selection. Journal of Alzheimer s Disease. 24(4). 721–738. 110 indexed citations
20.
Bertolazzi, Paola, Giovanni Felici, & Emanuel Weitschek. (2009). Learning to classify species with barcodes. BMC Bioinformatics. 10(S14). S7–S7. 72 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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