M. J. Sackin

2.5k total citations · 1 hit paper
24 papers, 2.0k citations indexed

About

M. J. Sackin is a scholar working on Molecular Biology, Plant Science and Food Science. According to data from OpenAlex, M. J. Sackin has authored 24 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 6 papers in Plant Science and 5 papers in Food Science. Recurrent topics in M. J. Sackin's work include Genomics and Phylogenetic Studies (4 papers), Plant Pathogens and Fungal Diseases (4 papers) and Genetic diversity and population structure (3 papers). M. J. Sackin is often cited by papers focused on Genomics and Phylogenetic Studies (4 papers), Plant Pathogens and Fungal Diseases (4 papers) and Genetic diversity and population structure (3 papers). M. J. Sackin collaborates with scholars based in United Kingdom, Nepal and France. M. J. Sackin's co-authors include P. H. A. Sneath, Michael Goodfellow, Grace Alderson, Suzanne T. Williams, Elizabeth M. H. Wellington, Stephen L. W. On, B. Holmes, Winifred Pennington, J. De Ley and K. Kersters and has published in prestigious journals such as Nature, New Phytologist and Systematic Biology.

In The Last Decade

M. J. Sackin

24 papers receiving 1.9k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Numerical Classification of Streptomyces and Related Genera

1983 1.1k citations Suzanne T. Williams, Michael Goodfellow et al. Microbiology profile →

Peers

M. J. Sackin

MB

PS

PHARM

CB

ECOLO

Ingrid Groth Germany

Einar Leifson United States

Zachary Charlop–Powers United States

Aaron A. Klammer United States

P. D. Bridge United Kingdom

James Drake United States

Patrick Marks United States

L.C. Reimer Germany

Einar Andreas Rødland Norway

Ingrid Groth Germany

M. J. Sackin

1.7k ×1.4

MB

503 ×0.6

PS

679 ×1.2

PHARM

345 ×1.0

CB

901 ×3.2

ECOLO

Citations per year, relative to M. J. Sackin M. J. Sackin (= 1×) peers Ingrid Groth

Countries citing papers authored by M. J. Sackin

Since Specialization

Citations

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

Fields of papers citing papers by M. J. Sackin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. J. Sackin. 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 M. J. Sackin. The network helps show where M. J. Sackin may publish in the future.

Co-authorship network of co-authors of M. J. Sackin

This figure shows the co-authorship network connecting the top 25 collaborators of M. J. Sackin. A scholar is included among the top collaborators of M. J. Sackin 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 M. J. Sackin. M. J. Sackin 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:

20 of 20 papers shown

1.

On, Stephen L. W., B. Holmes, & M. J. Sackin. (1996). A probability matrix for the identification of campylobacters, helicobacters and allied taxa. Journal of Applied Bacteriology. 81(4). 425–432. 113 indexed citations

2.

On, Stephen L. W., B. Holmes, & M. J. Sackin. (1996). A probability matrix for the identification of campylobacters, helicobacters and allied taxa. Journal of Applied Microbiology. 81(4). 425–432. 43 indexed citations

3.

Bridge, P. D. & M. J. Sackin. (1991). Stability of classification of filamentous fungi under changes in character coding strategy. Mycopathologia. 115(2). 105–111. 4 indexed citations

4.

Odds, Frank C., M. J. Sackin, & Dorothy Jones. (1990). Numerical taxonomic analysis of imperfect yeast species in Candida and Torulopsis shows no basis for generic separation. Journal of General Microbiology. 136(4). 761–765. 6 indexed citations

5.

Bridge, P. D., David L. Hawksworth, Z. Kozakiewicz, et al.. (1989). A Reappraisal of the Terverticillate Penicillia Using Biochemical, Physiological and Morphological Features II. Identification. Microbiology. 135(11). 2967–2978. 16 indexed citations

6.

Bridge, P. D., David L. Hawksworth, Z. Kozakiewicz, et al.. (1989). A Reappraisal of the Terverticillate Penicillia Using Biochemical, Physiological and Morphological Features I. Numerical Taxonomy. Microbiology. 135(11). 2941–2966. 54 indexed citations

7.

Williams, Suzanne T., Michael Goodfellow, Grace Alderson, et al.. (1983). Numerical Classification of Streptomyces and Related Genera. Microbiology. 129(6). 1743–1813. 1134 indexed citations breakdown →

8.

Williams, Suzanne T., Michael Goodfellow, Elizabeth M. H. Wellington, et al.. (1983). A Probability Matrix for Identification of some Streptomycetes. Microbiology. 129(6). 1815–1830. 145 indexed citations

9.

Sneath, P. H. A., Michael Stevens, & M. J. Sackin. (1981). Numerical taxonomy of Pseudomonas based on published records of substrate utilization. Antonie van Leeuwenhoek. 47(5). 423–448. 64 indexed citations

10.

Sneath, P. H. A. & M. J. Sackin. (1979). Basic program for printing a coding sheet for unknowns that are to be identified against an identification matrix of percent positive characters. Computers & Geosciences. 5(3-4). 359–367. 6 indexed citations

11.

Pennington, Winifred & M. J. Sackin. (1975). I. NUMERICAL ANALYSIS. New Phytologist. 75(2). 419–453. 90 indexed citations

12.

Kersters, K., J. De Ley, P. H. A. Sneath, & M. J. Sackin. (1973). Numerical Taxonomic Analysis of Agrobacterium. Journal of General Microbiology. 78(2). 227–239. 103 indexed citations

13.

Goodfellow, Michael, et al.. (1972). Numerical Classification of "Mycobacterium" rhodochrous and Runyon's Group IV Mycobacteria. International Journal of Systematic Bacteriology. 22(2). 81–98. 27 indexed citations

14.

Jones, Dorothy, M. J. Sackin, & P. H. A. Sneath. (1972). A Numerical Taxonomic Study of Streptococci of Serological Group D. Journal of General Microbiology. 72(3). 439–450. 28 indexed citations

15.

Sackin, M. J.. (1972). "Good" and "Bad" Phenograms. Systematic Biology. 21(2). 225–226. 99 indexed citations

16.

Goodfellow, Michael, et al.. (1971). A taxonomic study of Pasteurella and Actinobacillus strains.. PubMed. 69(3). 8–8. 4 indexed citations

17.

Sackin, M. J. & Daniel F. Merriam. (1969). Autoassociation, a new geological tool. Mathematical Geology. 1(1). 7–16. 5 indexed citations

18.

Ashworth, John & M. J. Sackin. (1969). Role of Aneuploid Cells in Cell Differentiation in the Cellular Slime Mould Dictyostelium discoideum. Nature. 224(5221). 817–818. 4 indexed citations

19.

Harbaugh, John W. & M. J. Sackin. (1968). FORTRAN IV Program for Harmonic Trend Analysis using Double Fourier Series and Regularly Gridded Data for the GE 625 Computer. Bulletin (Kansas Geological Survey). 1–30. 3 indexed citations

20.

Sackin, M. J., P. H. A. Sneath, & Daniel F. Merriam. (1965). ALGOL program for cross-association of nonnumeric sequences using a medium-size computer. Holmes Museum Of Anthropology (Wichita State University). 11 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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