Philip Tedder

729 total citations
7 papers, 276 citations indexed

About

Philip Tedder is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Philip Tedder has authored 7 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Cancer Research. Recurrent topics in Philip Tedder's work include Machine Learning in Bioinformatics (2 papers), Cancer Genomics and Diagnostics (2 papers) and Genomic variations and chromosomal abnormalities (2 papers). Philip Tedder is often cited by papers focused on Machine Learning in Bioinformatics (2 papers), Cancer Genomics and Diagnostics (2 papers) and Genomic variations and chromosomal abnormalities (2 papers). Philip Tedder collaborates with scholars based in United Kingdom, United States and Germany. Philip Tedder's co-authors include Stephen A. Krawetz, Martin H. Brinkworth, David Miller, Adrian E. Platts, Agnieszka Paradowska‐Gorycka, Klaus Steger, David Iles, David R. Westhead, James Bradford and Andrew J. Bulpitt and has published in prestigious journals such as Bioinformatics, The Plant Journal and Genome Research.

In The Last Decade

Philip Tedder

7 papers receiving 273 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Philip Tedder United Kingdom	6	198	111	102	75	45	7	276
Anne-Karen Faure France	6	311 1.6×	170 1.5×	173 1.7×	109 1.5×	46 1.0×	6	420
Maria João Pinho Portugal	7	155 0.8×	131 1.2×	115 1.1×	98 1.3×	87 1.9×	11	289
Steven L. Taylor United States	5	185 0.9×	228 2.1×	94 0.9×	187 2.5×	61 1.4×	6	434
T. Hansmann Germany	8	231 1.2×	25 0.2×	157 1.5×	83 1.1×	86 1.9×	10	319
Brittany L. Daughtry United States	7	121 0.6×	47 0.4×	56 0.5×	122 1.6×	103 2.3×	10	242
Tinke L. Vormer Netherlands	4	170 0.9×	166 1.5×	98 1.0×	121 1.6×	12 0.3×	6	320
Jun‐Shu Ai China	11	228 1.2×	84 0.8×	45 0.4×	234 3.1×	48 1.1×	12	345
Rosana Rodríguez‐Casuriaga Uruguay	10	240 1.2×	109 1.0×	105 1.0×	98 1.3×	13 0.3×	19	336
Namdori R. Mtango United States	12	233 1.2×	84 0.8×	70 0.7×	206 2.7×	57 1.3×	18	367
Suixing Fan China	8	235 1.2×	58 0.5×	76 0.7×	53 0.7×	11 0.2×	13	293

Countries citing papers authored by Philip Tedder

Since Specialization

Citations

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

Fields of papers citing papers by Philip Tedder

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philip Tedder

This figure shows the co-authorship network connecting the top 25 collaborators of Philip Tedder. A scholar is included among the top collaborators of Philip Tedder 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 Philip Tedder. Philip Tedder is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Ivakhno, Sergii, Eric Roller, Camilla Colombo, Philip Tedder, & Anthony J. Cox. (2017). Canvas SPW: calling de novo copy number variants in pedigrees. Bioinformatics. 34(3). 516–518. 9 indexed citations

2.

Ivakhno, Sergii, Camilla Colombo, Stephen Tanner, et al.. (2016). tHapMix: simulating tumour samples through haplotype mixtures. Bioinformatics. 33(2). 280–282. 7 indexed citations

3.

Tedder, Philip, James Bradford, Glenn A. McConkey, Andrew J. Bulpitt, & David R. Westhead. (2010). PlasmoPredict: a gene function prediction website for Plasmodium falciparum. Trends in Parasitology. 26(3). 107–110. 3 indexed citations

4.

Tedder, Philip, James Bradford, Chris J. Needham, et al.. (2010). Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum. Bioinformatics. 26(19). 2431–2437. 17 indexed citations

5.

Tedder, Philip, Elena Zubko, David R. Westhead, & Peter Meyer. (2009). Small RNA analysis in Petunia hybrida identifies unusual tissue-specific expression patterns of conserved miRNAs and of a 24mer RNA. RNA. 15(6). 1012–1020. 9 indexed citations

6.

Brinkworth, Martin H., David Iles, Stephen A. Krawetz, et al.. (2009). Endonuclease-sensitive regions of human spermatozoal chromatin are highly enriched in promoter and CTCF binding sequences. Genome Research. 19(8). 1338–1349. 217 indexed citations

7.

Bradford, James, Chris J. Needham, Philip Tedder, et al.. (2009). GO-At :in silicoprediction of gene function inArabidopsis thalianaby combining heterogeneous data. The Plant Journal. 61(4). 713–721. 14 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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