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.
Re-calculating the cost of coccidiosis in chickens
2020414 citationsR. Venu, M. Raman et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of M. Raman'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. Raman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Raman more than expected).
This network shows the impact of papers produced by M. Raman. 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. Raman. The network helps show where M. Raman may publish in the future.
Co-authorship network of co-authors of M. Raman
This figure shows the co-authorship network connecting the top 25 collaborators of M. Raman.
A scholar is included among the top collaborators of M. Raman 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. Raman. M. Raman is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Venu, R., et al.. (2013). Comparative evaluation of conventional diagnostic methods for detection of bovine cryptosporidiosis. The Indian Journal of Animal Sciences. 83(2).1 indexed citations
8.
Raman, M., et al.. (2013). DNA Extraction Protocols from Oocysts of Poultry eimeria. The Indian Veterinary Journal. 90(5). 102–105.1 indexed citations
Raman, M., et al.. (2011). Efficacy of Allium sativum Linn. against strongyles in naturally infected sheep. Journal of Veterinary Parasitology. 25(2). 124–128.1 indexed citations
11.
Vairamuthu, S., C. Balachandran, N. Pazhanivel, Senthil Kumar Karuppannan, & M. Raman. (2011). Occurrence of Trypanosoma Theileri Laveran, 1902 in a Holstein Friesian Cross-Bred Cow. Indian Journal of Animal Research. 45(4). 324–325.1 indexed citations
12.
Raman, M., et al.. (2009). Multiple anthelmintic resistance in gastrointestinal nematodes of sheep in Southern India. Veterinarski arhiv. 79(6). 611–620.19 indexed citations
Raman, M., et al.. (2005). Egg immunoglobulins - an alternative source of antibody for diagnosis of infectious bursal disease. Veterinarski arhiv. 75(1). 49–56.6 indexed citations
15.
Balachandran, C., N. Pazhanivel, S. Vairamuthu, et al.. (2005). Pathological Changes in Concurrent Onchocerca Gibsoni And Onchocerca Armillata Infestation in a Cow. Indian Journal of Veterinary Pathology. 29(2). 131–132.2 indexed citations
16.
Pazhanivel, N., et al.. (2004). PREVALENCE OF GASTRO-INTESTINAL HELMINTHS IN SHEEP OF DHARMAPURI DISTRICT (TAMILNADU). Indian Journal of Animal Research. 38(1). 53–55.2 indexed citations
Raman, M., et al.. (2001). In vitro survivability of strongylid larvae of elephants. The Indian Journal of Animal Sciences. 71(11). 1043–1044.2 indexed citations
19.
Raman, M., et al.. (2000). Strongylosis in captive elephants - a report.. Indian Journal of Animal Health. 39(2). 85–86.1 indexed citations
20.
Raman, M., et al.. (1998). Serodiagnosis of hydatidosis in sheep by counterimmunoelectrophoresis in Chennai, India *. The Indian Journal of Animal Sciences. 68(11). 1169–1170.4 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.