Sanja Tomić

Dr. Sanja Tomić

Division of Organic Chemistry and Biochemistry, Ruđer Bošković Institut, Bijnička 54, HR-10000 Zagreb, Croatia
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Research Focus & Metrics

Academic Career Length

27Years (2000-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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20 February 2008 in Acta Crystallographica Section D Structural Biology
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IDIvan Dokmanić
Ivan Dokmanić
MŠMile Šikić
Mile Šikić
STSanja Tomić
Sanja Tomić

9 April 2008 in BMC Structural Biology
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JMJosip Mihel
Josip Mihel
MŠMile Šikić
Mile Šikić
STSanja Tomić
Sanja Tomić
BJBranko Jeren
Branko Jeren
KVKristian Vlahoviček
Kristian Vlahoviček
Background: PSAIA (Protein Structure and Interaction Analyzer) was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results: In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm) for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion: In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

6 June 2012 in Journal of Medicinal Chemistry
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MAMaja Aleksić
Maja Aleksić
BBBranimir Bertoša
Branimir Bertoša
RNRaja Nhili
Raja Nhili
LULidija Uzelac
Lidija Uzelac
Ivana JarakIvana Jarak
Ivana Jarak
GKGrace Karminski-Zamola
Grace Karminski-Zamola

1 January 2008 in Biophysical Journal
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BBBranimir Bertoša
Branimir Bertoša
BKBiserka Kojić-Prodić
Biserka Kojić-Prodić
Rebecca WadeRebecca Wade
Rebecca Wade
STSanja Tomić
Sanja Tomić

1 December 2002 in Journal of Molecular Graphics and Modelling
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STSanja Tomić
Sanja Tomić
BKBiserka Kojić-Prodić
Biserka Kojić-Prodić

24 February 2012 in Chemistry – A European Journal
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LTLidija‐Marija Tumir
Lidija‐Marija Tumir
Ivo CrnolatacIvo Crnolatac
Ivo Crnolatac
TDTodor Deligeorgiev
Todor Deligeorgiev
AVAleksey Vasilev
Aleksey Vasilev
SKStefka Kaloyanova
Stefka Kaloyanova
Ivo PiantanidaIvo Piantanida
Ivo Piantanida