Research Articles

Sengottiyan S., Mikołajczyk A., Jagiełło K., Swirog M., Puzyn T. (2023): Core, Coating, or Corona? The Importance of Considering Protein Coronas in nano-QSPR Modeling of Zeta Potential. ACS Nano, 17, 3, 1989–1997. IF [5 years] = 18.022, MEiN = 200, link

Sengottiyan S., Mikołajczyk A., Puzyn T. (2023): How Does the Study MD of pH-Dependent Exposure of Nanoparticles Affect Cellular Uptake of Anticancer Drugs? International Journal of Molecular Sciences, 24(4), 3479. IF [5 years] = 6.628, MEiN = 140, link

Kowalska D., Sosnowska A., Bulawska N., Stępnik M., Besselink H., Behnisch P., & Puzyn T. (2023): How the structure of per- and polyfluoroalkyl substances (PFAS) influences their binding potency to the peroxisome proliferator-activated and thyroid hormone receptors - an in silico screening study. Molecules, 28, 1–24. IF [5 years] = 5.110, MEiN =140, link

Sosnowska A., Buławska N., Kowalska D., & Puzyn T. (2023): Towards higher scientific validity and regulatory acceptance of predictive models for PFAS. Green Chemistry, 25, 1261–1275. IF [5 years] = 9.905, MEiN = 200, link

Mikołajczyk A., Zhdan U., Antoniotti S., Smolinski A., Jagiełło K., Skurski P., Harb M., Puzyn T., & Polański J. (2023): Retrosynthesis from transforms to predictive sustainable chemistry and nanotechnology: a brief tutorial review. Green Chemistry, 1–21. IF [5 years] = 9.905, MEiN = 200, link

Del Giudice G., Serra A., Saarimäki L. A., Kotsis K., Rouse I., Colibaba S. A., ... & Greco D. (2023): An ancestral molecular response to nanomaterial particulates. Nature Nanotechnology, 1-10. IF [5 years] = 40.523, MEiN = 200, link

Kozlowska, L., Jagiello, K., Ciura, K., Sosnowska, A., Zwiech, R., Zbrog, Z., Wasowicz, W., and Gromadzinska, J. (2023): The Effects of Two Kinds of Dietary Interventions on Serum Metabolic Profiles in Haemodialysis Patients. Biomolecules 13, no. 5: 854. IF [5 years] = 6.191, MEiN = 100; link

Kathiravan A., Sengottiyan S., Puzyn T., Pushparathinam G., Susila P. A. & Jhonsi M. A. (2022): Rapid Colorimetric Discrimination of Cyanide Ions–Mechanistic Insights and Applications. Analytical Methods. 2022, 14, 518-525. IF = 2.896, MEiN = 70, link

Jagiełło K., Judzinska B., Sosnowska A., Lynch I., Halappanavar S. & Puzyn T. (2022): Using AOP-Wiki to support the ecotoxicological risk assessment of nanomaterials: first steps in the development of novel Adverse Outcome Pathways. Environmental Science: Nano,
DOI: 10.1039/d1en01127h. IF = 8.131, MEiN = 140, link

Kozłowska L., Santonen T., Duca R.C., Godderis L., Jagiełło K., Janasik B., Van Nieuwenhuyse A., Poels K., Puzyn T., Scheepers P.T.J., Sijko M., Silva M.J., Sosnowska A., Viegas S., Verdonck J. Wąsowicz W. (2022): HBM4EU Chromates Study: Urinary Metabolomics Study of Workers Exposed to Hexavalent Chromium. Metabolites, 12, 362. IF = 4.932, MEiN = 100, link

Jagiello Karolina and Ciura Krzesimir (2022): In vitro to in vivo extrapolation to support the development of the next generation risk assessment (NGRA) strategy for nanomaterials. Nanoscale. DOI: 10.1039/d2nr00664b; IF = 7.790, MEiN = 140, link

Gromelski Maciej, Stolinski Filip, Jagiello Karolina, Rybińska-Fryca Anna, Williams Andrew, Halappanavar Sabina, Vogel Ulla, Puzyn Tomasz (2022): AOP173 key event associated pathway predictor – online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis. Nanotoxicology. doi.org/10.1080/17435390.2022.2064250; IF = 6.612, MEiN = 140, link 

Selvaraj Sengottiyan, Kakoli Malakar, Arunkumar Kathiravan, Marappan Velusamy, Alicja Mikolajczyk and Tomasz Puzyn (2022): Integrated Approach to Interaction Studies of Pyrene Derivatives with Bovine Serum Albumin: Insights from Theory and Experiment. The Journal of Physical Chemistry B, 2022, https://doi.org/10.1021/acs.jpcb.2c00778;  IF = 2.991, MEiN = 140, link

Ewelina Wyrzykowska, Alicja Mikolajczyk, Iseult Lynch, Nina Jeliazkova, Nikolay Kochev, Haralambos Sarimveis, Philip Doganis, Pantelis Karatzas, Antreas Afantitis, Georgia Melagraki, Angela Serra, Dario Greco, Julia Subbotina, Vladimir Lobaskin, Miguel A. Bañares, Eugenia Valsami-Jones, Karolina Jagiello & Tomasz Puzyn (2022): Representing and describing nanomaterials in predictive nanoinformatics. Nature Nanotechnology, 1-9. IF = 42.230, MEiN = 200, link

Thwala M. M., Afantitis A., Papadiamantis A. G., Tsoumanis A., Melagraki G., Dlamini L. N., Ouma C.N.M, Ramasami P., Harris R., Puzyn T., Sanabria N., Lynch I, Gulumian M. (2021): Using the Isalos platform to develop a (Q) SAR model that predicts metal oxide toxicity utilizing facet-based electronic, image analysis-based, and periodic table derived properties as descriptors. Structural Chemistry, 1-12. (OA); IF [2020] = 1.887; IF [5 years] = 1.494; MNISW = 40, link

Michalska-Ciechanowska A., Hendrysiak A., Brzezowska J., Wojdyło A. & Gajewicz-Skretna A. (2021): How Do the Different Types of Carrier and Drying Techniques Affect the Changes in Physico-Chemical Properties of Powders from Chokeberry Pomace Extracts?. Foods, 10(8), 1864. IF [2020] = 4.35, IF [5 years] = 4.957, MNiSW = 100, link

Gulumian M., Andraos Ch., Afantitis A., Puzyn T., Coville N.J. (2021): Importance of Surface Topography in Both Biological Activity and Catalysis of Nanomaterials: Can Catalysis by Design Guide Safe by Design? International Journal of Molecular Sciences, 22(15), 8347.
IF [2020] = 5.923, IF [5 years] = 6.132, MNiSW = 140, link

Sizochenko N., Mikolajczyk A., Syzochenko M., Puzyn T., Leszczynski J. (2021): Zeta potentials (ζ) of metal oxide nanoparticles: A meta-analysis of experimental data and a predictive neural networks modeling. NanoImpact, 22, 100317. IF [2020] = 5.316, IF [5 years] = 6.305, MNiSW = 100, link

Rudnicki-Velasquez P. B., Storoniak H., Jagiełło K., Kreczko–Kurzawa J., Jankowska M., Krzymiński K. J. (2021): Comparative studies on vitamin B1 deficiency in whole blood of chronically haemodialysed patients: chromatographic, fluorimetric and PCA study. Journal of Chromatography B, 1180, 122880. IF [2019] = 3.004, IF [5 years] = 2.841, MNiSW = 70, link

Jagiello, K., Halappanavar, S., Rybińska-Fryca, A., Williams, A., Vogel, U., Puzyn, T. (2021): Transcriptomics-based and AOP-informed structure-activity relationships to predict pulmonary pathology induced by multiwalled carbon nanotubes”. Small, Doi: 10.1002/smll.202003465. IF [2019] = 11.459; IF [5 years] = 10.611; MNISW = 200, link

Gajewicz‐Skretna A., Kar S., Piotrowska M., Leszczynski J. (2021): The kernel‐weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models. Journal of Cheminformatics 13:9. https://doi.org/10.1186/s13321‐021‐00484‐5. IF [2019] = 5,326; IF [5 years] = 5,687; MNISW = 100, link

Sizochenko N., Mikolajczyk A., Syzochenko M., Puzyn T., Leszczynski J. (2021): Zeta potentials (ζ) of metal oxide nanoparticles: A meta-analysis of experimental data and a predictive neural networks modeling. NanoImpact, 22, 100317, ISSN 2452-0748. IF[2019] = 5.478, IF[5 years] = 5.533, MNiSW = 100, link

Gajewicz-Skretna A., Furuhama A., Yamamoto H., Suzuki N. (2021): Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods. Chemosphere, 280, 130681.  IF [2019] = 5.778, IF [5 years] = 5.705, MNiSW = 100, link

Murugadoss S., Vinković Vrček I., Pem B., Jagiello K., Judzinska B., Sosnowska A., Martens M., Willighagen E.L., Puzyn T., Dusinska M., Cimpan M.R., Fessard V. and Hoet P.H. (2021): A Strategy Towards the Generation of Testable Adverse Outcome Pathways for Nanomaterials.
ALTEX 38(#), ###-###. doi:10.14573/altex.2102191, link

Lewandowski, Ł.; Gajewicz-Skretna, A.; Klimczuk, T.; Trykowski, G.; Nikiforow, K.; Lisowski, W.; Gołąbiewska, A.; Zaleska-Medynska, A. (2021): Towards Computer-Aided Graphene Covered TiO2-Cu/(CuxOy) Composite Design for the Purpose of Photoinduced Hydrogen Evolution. Catalysts, 11, 698. https://doi.org/10.3390/catal11060698, link

Jeliazkova N., Apostolova M. D., Andreoli C., Barone F., Barrick A., Battistelli C., Bossa C., Botea-Petcu a., Chatel A., De Angelis I., Dusinska M., El Yamani N., Gheorghe D., Giusti A., Gomez-Fernandez P., Grafstrom R., Gromelski M., Jacobsen N.R., Jeliazkov V., Jensen K.a., Kochev N., Kohonen P., Manier N., Mariussen E., Mech A., Navas J.M., Paskaleva V., Precupas A., Puzyn T., Rasmussen K., Ritchie P., Rodriguez Llopis I., Runden-Pran E., Sandu R., Shandilya N., Tanasescu S., Haase A. & Nymark, P. (2021): Towards FAIR nanosafety data. Nature Nanotechnology, 1-11. IF [2019] = 31.538, IF [5 years] = 40.301, MNiSW = 200, link

Afantitis A., Melagraki G., Isigonis P., Tsoumanis A., Varsou D.D., Valsami-Jones E., Papadiamantis A., Ellis L-J.A., Sarimveis H., Doganis P., Karatzas P., Tsiros P., Liampa I., Lobaskin V., Greco D., Serra A., Kinaret P.A.S., Saarimäki L.A., Grafström R., Kohonen P., Nymark P., Willighagen E., Puzyn T., Rybinska-Fryca A., Lyubartsev A., Jensen K.A., Brandenburg J.G., Lofts S., Svendsen C., Harrison S., Maier D., Tamm K., Jänes J., Sikk J., Dusinska M., Longhin E., Rundén-Pran E., Mariussen E., El Yamani N., Unger W., Radnik J., Tropsha A., Cohen Y., Leszczynski J., Hendren Ch.O., Wiesner M., Winkler D., Suzuki N., Yoon T.H., Choi J-S., Sanabria N., Gulumian M., Lynch I. (2020): NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment. Computational and Structural Biotechnology Journal, 18, 583-602. IF [2018] = 4.72, MNiSW = 10, link 

Serra A., Fratello M., Cattelani L., Liampa I., Melagraki G., Kohonen P., Nymark P., Federico A., Kinaret P.A.S. , Jagiello K., Kieu M., Choi J-S., Sanabria N., Gulumian M., Puzyn T., Yoon T-H., Sarimveis H., Grafström R., Afantitis A., Greco D. (2020): Transcriptomics in Toxicogenomics, Part III: Data Modelling for Risk Assessment. Nanomaterials, 10, 708. IF [2018] = 4.034, IF [5 years] = 4.358, MNiSW = 70, link

Kinaret P.A.S., Serra A., Federico A., Kohonen P., Nymark P., Liampa I., Kieu M., Choi J-S.,  Jagiello K., Sanabria N., Melagraki G., Cattelani L., Fratello M., Sarimveis H., Afantitis A., Yoon T-H., Gulumian M., Grafström R., Puzyn T., Greco D. (2020): Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects. Nanomaterials, 10, 4. IF [2018] = 4.034, IF [5 years] = 4.358, MNiSW = 70, link

Federico A., Serra A., Kieu Ha M., Kohonen P., Choi J-S., Liampa I., Nymark P., Sanabria N., Cattelani L., Fratello M., Kinaret P., A., S., Jagiello K., Puzyn T., Melagraki G., Gulumian M., Afantitis A., Sarimveis H., Yoon T-H., Grafström R., Greco D. (2020): Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data. Nanomaterials,10, 903. IF [2018] = 4.034, IF [5 years] = 4.358, MNiSW = 70, link

Rybinska-Fryca A., Mikolajczyk A., Luczak J., Paszkiewicz-Gawron M., Paszkiewicz M., Zaleska-Medynska A., Puzyn T. (2020): How thermal stability of ionic liquids leads to more efficient TiO₂-based nanophotocatalysts: Theoretical and experimental studies. Journal of Colloid and Interface Science, 572, 396-407. IF [2018] = 6.361, IF [5 years] = 5.078, MNiSW = 100, link

Rybinska-Fryca A., Sosnowska A., Puzyn T. (2020): Representation of the Structure – A Key Point of Building QSR/QSPR Models for Ionic Liquids. Materials 2020, 13(11), 2500. IF [2018] = 2.972, IF [5 years] = 3.532, MNiSW = 140, link

Sosnowska A., Laux E., Keppner H., Puzyn T., Bobrowski M. (2020): Relatively high-Seebeck thermoelectric cells containing ionic liquids supplemented by cobalt redox couple. Journal of Molecular Liquids 2020, 316(10), 113871. IF [2019]= 5.065, IF [5 years] = 4.766, MNiSW = 100, link

Isigonis, P., Afantitis, A., Antunes, D., Bartonova, A., Beitollahi, A., Bohmer, N., ... & Doak, S. (2020). Risk Governance of Emerging Technologies Demonstrated in Terms of its Applicability to Nanomaterials. Small, 2003303. IF [2019] = 11.459, IF [5 years] = 10.611, MNiSW = 200, link

Rybińska-Fryca A., Mikołajczyk A., Puzyn T. (2020): Structure–activity prediction networks (SAPNets): a step beyond Nano-QSAR for effective implementation of the safe-by-design concept. Nanoscale, IF [2019] = 6.895, IF [5 years] = 7.315, MNiSW = 140, link

Malankowska A., Mikołajczyk A., Mędrzycka J., Wysocka I., Nowaczyk G., Jarek M., Puzyn T., Mulkiewicz E. (2020): The effect of Ag, Au, Pt and Pd on the surface properties, photoatalytic activity and toxicity of multicomponent TiO₂-based nanomaterials. Environmental Science Nano, 7, 3557. IF [2019]: 7.683, IF [5 years] = 7.913, MNiSW = 140, link

Miodyńska M., Mikołajczyk A., Bajorowicz B., Zwara J., Klimczuk T., Lisowski W., Trykowski G., Pinto H. P., Zaleska-Medynska A.: (2020) Urchin-like TiO₂ structures decorated with lanthanide-doped Bi₂S₃ quantum dots to boost hydrogen photogeneration performance. Applied Catalysis B: Environmental, 272 (2020), 118962. IF [16.683], IF [5 years] = 14.443, MNiSW = 200, link 

Parnicka P., Mikołajczyk A., Pinto H. P., Lisowski W., Klimczuk T., Trykowski G., Bajorowicz B., Zaleska-Medyńska A. (2020): Experimental and DFT insights into an eco-friendly photocatalytic system toward environmental remediation and hydrogen generation based on AgInS₂ quantum dots embedded on Bi₂WO₆. Applied Surface Science, 525 (2020) 146596. IF [2019] = 6.182, IF [5 years] = 5.141, MNiSW = 140, link

Mazierski P., Mikołajczyk A., Grzyb T., Caicedo P. N. A., Wei Z., Kowalska E., Pinto H. P., Zaleska-Medynska A., Nadolna J. (2020): On the excitation mechanism of visible responsible Er-TiO₂ system proved by experimental and theoretical investigations for boosting photocatalytic aktivity. Applied Surface Science 527 (2020) 146815. IF [2019] = 6.182, IF [5 years] = 5.141, MNiSW = 140, link

Bajorowicz B., Mikolajczyk A., Pinto H.P., Miodynska M., Lisowski W., Klimczuk T., Kaplan-Ashiri I., Kazes M., Oron D., Zaleska-Medynska A. (2020): Integrated Experimental and Theoretical Approach for Efficient Design and Synthesis of Gold-Based Double Halide Perovskites. Journal of Physical Chemistry C, 124, 49, 26769–26779. IF [2019] = 4.189, IF [5 years] = 4.404, MNiSW = 140, link 

Giusti A., Atluri R., Tsekovska R., Gajewicz A., Apostolova M. D., Battistelli C. L., Bleeker A. J., Bossa C., Bouillard J., Dusinska M., Gómez-Fernández, P., Grafström R., Gromelski M., Handzhiyski Y., Jacobsen N. R., Jantunenm P., Jensen K. A., Mech A., Navas H. M., Nymark P., Oomen A. G., Puzyn T., Rasmussen K., Riebeling C., Rodriguez-Llopis I., Sabella S., Sintes J. R., Suarez-Merino B., Tanasescu S., Wallin H., Haase A (2019): Nanomaterial grouping: Existing approaches and future recommendations. NanoImpact (16), 100182. IF[2018]=5.52, MNiSW=70, link

Ambure P., Gajewicz-Skretna A., Cordeiro M. N. D., & Roy K. (2019): New Workflow for QSAR Model Development from Small Data Sets: Small Dataset Curator and Small Dataset Modeler. Integration of Data Curation, Exhaustive Double Cross-Validation, and a Set of Optimal Model Selection Techniques. Journal of chemical information and modeling, 59(10), 4070-4076. IF [2018] = 3.966, IF [5 years] = 4.297, MNiSW = 100, link

Sosnowska A., Brzeski J., Skurski P., Puzyn T. (2019): The Acid Strength of the Lewis‐Brønsted Superacids – A QSPR Study. Molecular Informatics, vol. 38, nr 8-9, 2019, pp 1-9. IF [2018] = 2.375, IF [5 years] = 1.895, MNiSW = 70, link

Mazierski P., Caicedo P.N.A., Grzyb T., Mikołajczyk A., Roy J.K., Wyrzykowska E., Wei Z., Kowalska E., Puzyn T., Zaleska-Medynska A., Nadolna J. (2019): Experimental and computational study of Tm-doped TiO2: The effect of Li+ on Vis-respones photocatalysis and luminescence. Applied Catalysis B: Environmental, 252, 138-151. IF [2018] = 14.229, IF [5 years] = 12.176, MNiSW = 200, link

Acharya K., Werner D., Dolfing J., Barycki M., Meynet P., Mrozik W., Komolafe O., Puzyn T., Davenport R. (2019): A quantitative structure-biodegradation relationship (QSBR) approach to predict biodegradation rates of aromatic chemicals. Water Research, 157, 181-190. 
IF [2018] =  7.913, IF [5 years] = 8.424, MNiSW = 140, link

Wyrzykowska E., Rybińska-Fryca A., Sosnowska A., Puzyn T. (2019): Virtual screening in the design of ionic liquids as environmentally safe bactericides. Green Chemistry, vol. 21, no. 8, 2019, ss. 1965-1973. IF [2018] = 9.405, IF [5 years] = 9.593, MNiSW = 200, link

Mikolajczyk, A., Sizochenko, N., Mulkiewicz, E., Malankowska, A., Rasulev, B., & Puzyn, T. (2019): A chemoinformatics approach for the characterization of hybrid nanomaterials: safer and efficient design perspective. Nanoscale, 11, 11808-11818. IF [2018] = 6.970, IF [5 years] = 7.592, MNiSW = 140, link

Jakubus A., Gromelski M., Jagiello K., Puzyn T., Stepnowski P., Paszkiewicz M. (2019): Dispersive solid-phase extraction using multi-walled carbon nanotubes combined with liquid chromatography–mass spectrometry for the analysis of β-blockers: Experimental and theoretical studies. Microchemical Journal, 146, 258-269. IF [2018] = 3.206, IF [5 years] = 2.993, MNiSW = 70, link

Jakubus A., Godlewska K., Gromelski M., Jagiello K., Puzyn T., Stepnowski P., Paszkiewicz M. (2019): The possibility to use multi-walled carbon nanotubes as a sorbent for dispersive solid phase extraction of selected pharmaceuticals and their metabolites: Effect of extraction condition. Microchemical Journal, 146, 1113-1125. IF [2018] = 3.206, IF [5 years] = 2.993, MNiSW = 70, link

Ambure P., Bhat J., Puzyn T. & Roy K. (2018/2019): Identifying natural compounds as multi-target-directed ligands against Alzheimer’s disease: an in silico approach. Journal of Biomolecular Structure and Dynamics, 1-25. IF [2018] = 3.310, IF [5 years] = 2.689, MNiSW = 70, link

Barycki M., Sosnowska A. & Puzyn T. (2018): AquaBoxIL–computational tool for determining the environmental distribution profile for ionic liquids. Green Chemistry, 2018, 20, 3359. IF [2018] = 9.405, IF [5 years] = 9.593, MNiSW = 45, link

Barycki M., Sosnowska A., Jagiello K., Puzyn T. (2018): Multi-Objective Genetic Algorithm (MOGA) As a Feature Selecting Strategy in the Development of Ionic Liquid’s Quantitative Toxicity – Toxicity Relationship Models. Journal of Chemical Information and Modeling, 58 (12), 2467-2476. IF [2018] = 3.966, IF [5 years] = 4.297, MNiSW = 40, link

Oberbek P., Bolek T., Chlanda A., Hirano S., Kusnieruk S., Rogowska-Tylman J., Nechyporenko G., Zinchenko V., Swieszkowski W., Puzyn T. (2018): Characterization and influence of hydroxyapatite nanopowders on living cells. Beilstein Journal of Nanotechnology, 9, 3079-3094.
IF [2018] = 2.269, IF [5 years] = 3.025, MNiSW = 35, link

Stone, V., Führ, M., Feindt, P. H., Bouwmeester, H., Linkov, I., Sabella, S. & Fito, C. (2018): The Essential Elements of a Risk Governance Framework for Current and Future Nanotechnologies. Risk Analysis, vol. 38, nr 7, ss. 1321-1331. IF [2018] = 2.564, IF [5 years] = 3.161, MNiSW = 40, link

Gajewicz A., Puzyn T., Odziomek K., Urbaszek P., Haase A., Riebeling C. & Bouwmeester H. (2018): Decision tree models to classify nanomaterials according to the DF4nanoGrouping scheme. Nanotoxicology, vol. 12, nr 1, ss. 1-17. IF [2018] = 5.955, IF [5 years] = 5.998, MNiSW = 45, link

Gajewicz, A. (2018): How to judge whether QSAR/read-across predictions can be trusted: a novel approach for establishing a model's applicability domain. Environmental Science: Nano, vol. 5, nr 2, ss. 408-421. IF [2018] = 7.704, IF [5 years] = 8.009, MNiSW = 40, link

Mikolajczyk A., Gajewicz A., Mulkiewicz E., Rasulev B., Marchelek M., Diak M., Hirano S., Zaleska-Medynska A & Puzyn T. (2018): Nano-QSAR modeling for ecosafe design of heterogeneous TiO 2-based nano-photocatalysts. Environmental Science: Nano, vol. 5, nr 5, ss. 1150-1160.
IF [2018] = 7.704, IF [5 years] = 8.009, MNiSW = 40, link

Krukowska A., Trykowski G., Winiarski M. J., Klimczuk T., Lisowski W., Mikolajczyk A., Pinto H.P. & Zaleska-Medynska A. (2018): Mono- and bimetallic nanoparticles decorated KTaO3 photocatalysts with improved Vis and UV–vis light activity. Applied Surface Science, (441) 993-1011. IF [2018] = 5.155, IF [5 years] = 4.281, MNiSW = 35, link

Krukowska A., Winiarski M. J., Strychalska-Nowak J., Klimczuk T., Lisowski W., Mikolajczyk A., Pinto H.P., Puzyn T., Grzyb T. & Zaleska-Medynska A. (2018): Rare earth ions doped K2Ta2O6 photocatalysts with enhanced UV–vis light activity. Applied Catalysis B: Environmental, (224) 451-468. IF [2018] = 14.229, IF [5 years] = 12.176, MNiSW = 45, link

Sizochenko N., Mikolajczyk A., Jagiello K., Puzyn T., Leszczynski J. & Rasulev B. (2018): How the toxicity of nanomaterials towards different species could be simultaneously evaluated: a novel multi-nano-read-across approach. Nanoscale, 10(2), 582-591.
IF [2018] = 6.970, IF [5 years] = 7.592, MNiSW = 40, link

Jagiello K., Makurat S., Pereć S., Rak J. & Puzyn T. (2018): Molecular features of thymidine analogues governing the activity of human thymidine kinase. Structural Chemistry, vol. 29, nr 5, ss. 1367-1374. IF [2018] = 1.624, IF [5 years] = 1.333, MNiSW = 25, link

Puzyn T., Jeliazkova N., Sarimveis H., Robinson RLM., Lobaskin V., Rallo R., Richarz AN., Gajewicz A., Papadopulos MG., Hastings J., Cronin MTD., Benfenati E., Fernandez A. (2018): Perspectives from the NanoSafety Modelling Cluster on the validation criteria for (Q)SAR models used in nanotechnology. Food and Chemical Toxicology, 112, 478-494. IF [2018] = 3.775, IF [5 years] = 4.248, MNiSW = 40, link

Mazierski P., Mikołajczyk A., Bajorowicz B., Malanowska A., Zaleska-Medynska A., Nadolna J. (2018): The role of lanthanides in TiO2-based photocatalysis: A review. Applied Catalysis B-Environmental, 233, 301-317. IF [2018] = 14.229, IF [5 years] = 12.176, MNiSW = 45, link

Kulthong K., Duivenvoorde L., Mizera B. Z., Rijkers D.,b ten Dam G., Oegema G., Puzyn T., Bouwmeester H., van der Zande M. (2018): Implementation of a dynamic intestinal gut-on-a-chip barrier model for transport studies of lipophilic dioxin congeners. RSC Advances, 2018, 8, 32440. IF [2018] = 3.049, IF [5 years] = 3.168, MNiSW = 35, link

Judycka U., Jagiello K., Gromelski M., Bober L., Błażejowski J., Puzyn T. (2018): Chemometric outlook on correlations between retention parameters of polar and semi-polar HPLC columns and physicochemical characteristics of ampholytic substances of biological and pharmaceutical relevance. Structural Chemistry, 2018. IF [2018] = 1.624, IF [5 years] = 1.333, MNiSW = 25, link

Judycka U., Jagiello K., Gromelski M., Bober L., Błażejowski J., Puzyn T. (2018): Chemometric approach to correlations between retention parameters of non-polar HPLC columns and physicochemical characteristics for ampholytic substances of biological and pharmaceutical relevance. Journal of Chematography B, 2018, 1095, 8-14. IF [2018] = 2.813, IF [5 years] = 2.751, MNiSW = 30, link

Judycka U., Jagiello K., Bober L., Błażejowski J., Puzyn T. (2018): Assessing therapeutic relevance of biologically interesting, ampholytic substances based on their physicochemical and spectral characteristics with chemometric tools. Chemical Physics Letters, 2018, 701, 58-64.
IF [2018] = 1.901, IF [5 years] = 1.696, MNiSW = 30, link

Sizochenko N., Gajewicz A., Leszczyński J., Puzyn T. (2018): Reply to the comment on „Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models“ by D.A. Tasi, J. Csontos, B. Nagy, Z. Kónya and G. Tasi. Nanoscale, 2018, 10, C8NR02377H. Nanoscale, 2018. IF [2018] = 6.970, IF [5 years] = 7.592, MNiSW = 40, link

Rybińska A., Sosnowska A., Grzonkowska M., Barycki M., Puzyn T. (2017): Comment on „Filling environmental data gaps with QSPR for ionic liquids: Modeling n-octanol/water coefficient”. Journal of Hazardous Materials, vol. 329, 2017, pp 351-352. [IF2018 = 7.65, IF5 years = 7.336, MNiSW = 200] link

Gajewicz A., Jagiello K., Cronin M. T. D., Leszczynski J., Puzyn, T. (2017): Addressing a bottle neck for regulation of nanomaterials: quantitative read-across (Nano-QRA) algorithm for cases when only limited data is available. Environmental Science: Nano, 4, 346-358. [IF 2015 = 5.896, IF5 years = 5.896, MNiSW = 40] link

Jagiello K., Sosnowska A., Kar S., Demkowicz S., Daśko M., Leszczynski J., Rachon J. and Puzyn, T. (2017): Geometry optimization of steroid sulfatase inhibitors-the influence on the free binding energy with STS. Structural Chemistry, pp.1-16. [IF2015 = 1.854, IF5 years = 1.566, MNiSW = 25] link

Mazierski P., Lisowski W., Grzyb T., Winiarski M.J., Klimczuk T., Mikołajczyk A., Flisikowski J., Hirsch A., Kołakowska A., Puzyn, T. and Zaleska-Medynska A. (2017): Enhanced photocatalytic properties of lanthanide-TiO 2 nanotubes: An experimental and theoretical study. Applied Catalysis B: Environmental, 205, pp.376-385. IF2015 = 8.328, IF5 years = 8.142, MNiSW = 45] link

Barycki M., Sosnowska A., Puzyn T. (2017): Which structural features stand behind micelization of ionic liquids? Quantitative Structure-Property Relationship studies. Journal of Colloid and Interface Science, 487, 475-483 [IF2015 = 3.782, IF5 years = 3.758, MNiSW = 30] link

Sizochenko N., Syzochenko M., Gajewicz A., Leszczynski J. and Puzyn T. (2017): Predicting Physical Properties of Nanofluids by Computational Modeling. Journal of Physical Chemistry C, 121, 1910-1917. [IF2015 = 4.509, IF5 years = 4.919, MNiSW = 35] link

Urbaszek P., Gajewicz A., Sikorska C., Haranczyk M., & Puzyn T. (2017): Modeling adsorption of brominated, chlorinated and mixed bromo/chloro-dibenzo-p-dioxins on C60 fullerene using Nano-QSPR. Beilstein Journal of Nanotechnology, 8(1), 752-761. [IF2015 = 2.778, IF5 years = 2.977, MNiSW = 35] link

Kotłowska, A., Puzyn, T., Sworczak, K., Stepnowski, P., & Szefer, P. (2017). Metabolomic Biomarkers in Urine of Cushing’s Syndrome Patients. International Journal of Molecular Sciences, 18(2), 294. [IF2015 = 3.257, IF5 years = 3.213, MNiSW = 30] link

Fjodorova N., Novic M., Gajewicz A. & Rasulev B. (2017): The way to cover prediction for cytotoxicity for all existing nano-sized metal oxides by using neural network method. Nanotoxicology, (just-accepted), 1-28. [IF2015 = 7.913, IF5 years = 8.137, MNiSW = 45] link

Odziomek K., Ushizima D., Oberbek P., Kurzydłowski K. J., Puzyn T. & Haranczyk M. (2017): Scanning electron microscopy image representativeness: morphological data on nanoparticles. Journal of microscopy, 265(1), 34-50. [IF2015 = 2.136, IF5 years = 2.034, MNiSW = 35] link 

Sosnowska A., Grzonkowska M. & Puzyn T. (2017): Global versus local QSAR models for predicting ionic liquids toxicity against IPC-81 leukemia rat cell line: The predictive ability. Journal of Molecular Liquids, 231, 333-340. [IF2015 = 2.740, IF5 years = 2.439, MNiSW = 30] link

Giełdoń A., Witt M. M., Gajewicz A., & Puzyn T. (2017): Rapid insight into C60 influence on biological functions of proteins. Structural Chemistry, 1-14. [IF2015 = 1.854, IF5 years = 1.566, MNiSW = 25] link

Jagiello K., Chomicz B., Avramopoulos A., Gajewicz A., Mikolajczyk A., Bonifassi P., Papadopoulos M.G., Leszczynski J. and Puzyn, T. (2017): Size-dependent electronic properties of nanomaterials: How this novel class of nanodescriptors supposed to be calculated? Structural Chemistry, 1-9. IF [2015] = 1.854, IF [5 years] = 1.566, MNiSW = 25

Gajewicz A. (2017): Development of valuable predictive read-across models based on “real-life” (sparse) nanotoxicity data. Environmental Science: Nano, 2017, 4, 1389-1403. [IF2015 = 5.896, IF5 years = 5.896, MNiSW = 40] link

Gajewicz, A. (2017): What if the number of nanotoxicity data is too small for developing predictive Nano-QSAR models? An alternative read-across based approach for filling data gaps. Nanoscale, 2017, 9, 8435-8448. [IF2016 = 7.367, IF5 years = 7.668, MNiSW = 40] link

Bañares M. A., Haase A., Tran L., Lobaskin V., Oberdörster G., Rallo R., Leszczynski J., Hoet P., Korenstein R., Hardy B. & Puzyn T. (2017): CompNanoTox2015: novel perspectives from a European conference on computational nanotoxicology on predictive nanotoxicology. Nanotoxicology, 1-7. [IF 2016 = 6.428, IF5 years = 6.327, MNiSW = 45] link

Mikolajczyk A., Sizochenko N., Mulkiewicz E., Malankowska A., Nischk M., Jurczak P., ... & Gajewicz A. (2017): Evaluating the toxicity of TiO2-based nanoparticles to Chinese hamster ovary cells and Escherichia coli: a complementary experimental and computational approach. Beilstein Journal of Nanotechnology, 8(1), 2171-2180. [IF 2016 = 3.127, IF5 years = 3.070, MNiSW = 30] link

Jagiello K., Chomicz B., Avramopoukos A., Gajewicz A., Mikolajczyk A., Bonifassi P., Papadopoulos M.G., Leszczynski J., Puzyn T. (2016): Size-dependent electronic properties of nanomaterials: How this novel class of nanodescriptors supposed to be calculated? Structural Chemistry, 1-9, DOI: 10.1007/s11224-016-0838-2. [IF2015 = 1.854; IF5years = 1.566; MNiSW2015 = 25] link

Jagiello K., Grzonkowska M., Swirog M., Ahmed L., Rasulev B., Avramopoulos A., Papadopoulos M. G., Leszczynski J., Puzyn T. (2016): Advantages and limitations of classic and 3D QSAR approaches in nano-QSAR studies based on biological activity of fullerene derivatives. Journal of Nanoparticle Research 18, First OnLine DOI: 10.1007/s11051-016-3564-1. [IF2015 = 2.101; IF5years = 2.499; MNiSW2015 = 30] link

Mikolajczyk A., Malankowska A., Nowaczyk G., Gajewicz A., Hirano S., Jurga S.,   Zaleska-Medynska A., Puzyn T. (2016): Combined experimental and computational approach to developing efficient photocatalysts based on Au/Pd–TiO2 nanoparticles. Environmental Science: Nano, 3, 1425-1435. [IF2015 = 5.896; IF5years = 5.896; MNiSW2015 = 40] link

Wyrzykowska E., Mikolajczyk A., Sikorska C., Puzyn T.  (2016): Development of a novel in silico model of zeta potential for metal oxide nanoparticles: a nano-QSPR approach. Nanotechnology 27, 445702. [IF2015 = 3.573; IF5years = 3.611; MNiSW2015 = 35] link

Sosnowska A., Barycki M., Gajewicz A., Bobrowski M., Freza S., Skurski P., Uhl S., Laux E., Journot T., Jeandupeux L., Keppner H., Puzyn T. (2016): Towards the Application of Structure-Property Relationship Modeling in Materials Science: Predicting the Seebeck Coefficient for Ionic Liquid/Redox Couple Systems. ChemPhysChem 17, 1591-1600. [IF2015 = 3.138; IF5years = 3.130; MNiSW2015 = 35] link

Sizochenko N., Gajewicz A., Leszczynski J., Puzyn T. (2016): Causation or only correlation? Application of causal inference graphs for evaluating causality in nano-QSAR models. Nanoscale 8, 7203-7208. [IF2015 = 7.760; IF5years = 7.915; MNiSW2015 = 40] link

Sikorska C., Gajewicz A., Urbaszek P., Lubinski L., Puzyn T. (2016): Efficient way of designing fullerene derivatives based on simplified DFT calculations and QSPR modeling. Chemometrics and Intelligent Laboratory Systems 152, 125-133. [IF2015 = 2.217; IF5years = 2.595; MNiSW2015 = 35] link

Rybinska A., Sosnowska A., Grzonkowska M., Barycki M., Puzyn T. (2016): Filling environmental data gaps with QSPR for ionic liquids: Modeling n-octanol/water coefficient. Journal of Hazardous Materials 303, 137-144. [IF2015 = 4.836; IF5years = 5.641; MNiSW2015 = 45] link

Rybinska A., Sosnowska A., Barycki M., Puzyn T. (2016): Geometry optimization method versus predictive ability in QSPR modeling for ionic liquids. Journal of Computer-Aided Molecular Design 30, 165-176. [IF2015 = 3.199; IF5years = 2.998; MNiSW2015 = 30] link

Robinson R. L. M., Lynch I., Peijnenburg W., Rumble J., Klaessig F., Marquardt C., Rauscher H., Puzyn T., Purian R., Aberg C., Karcher S., Vriens H., Hoet P., Hoover M. D., Hendren C. O., Harper S. L. (2016): How should the completeness and quality of curated nanomaterial data be evaluated? Nanoscale 8, 9919-9943. [IF2015 = 7.760; IF5years = 7.915; MNiSW2015 = 40] link

Kar S., Gajewicz A., Roy K., Leszczynski J., Puzyn T.  (2016): Extrapolating between toxicity endpoints of metal oxide nanoparticles: Predicting toxicity to Escherichia coli and human keratinocyte cell line (HaCaT) with Nano-QTTR. Ecotoxicology and Environmental Safety 126, 238-244. [IF2015 = 3.130; IF5years = 3.246; MNiSW2015 = 30] link

Grzonkowska M., Sosnowska A., Barycki M., Rybinska A., Puzyn T. (2016): How the structure of ionic liquid affects its toxicity to Vibrio fischeri? Chemosphere 159, 199-207. [IF2015 = 3.698; IF5years = 4.068; MNiSW2015 = 35] link

Barycki M., Sosnowska A., Piotrowska M., Urbaszek P., Rybinska A., Grzonkowska M., Puzyn T. (2016): ILPC: simple chemometric tool supporting the design of ionic liquids. Journal of Cheminformatics 8, 8-40. [IF2015 = 3.949; IF5years = 5.944; MNiSW2015 = 40] link

Barycki M., Sosnowska A., Gajewicz A., Bobrowski M., Wilenska D., Skurski P., Gieldon A., Czaplewski C., Uhl S., Laux E., Journot T., Jeandupeux L., Keppner H., Puzyn T. (2016): Temperature-dependent structure-property modeling of viscosity for ionic liquids. Fluid Phase Equilibria 427, 9-17. [IF2015 = 1.846; IF5years = 1.987; MNiSW2015 = 30] link

Cassano A., Marchese Robinson R.L., Palczewska A., Puzyn T., Gajewicz A., Tran L., Manganelli S., Cronin M.T.D. (2016): Comparing the CORAL and Random Forest Approaches for Modelling the In Vitro Cytotoxicity of Silica Nanomaterials. ATLA 44, 533-556, 2016. [IF2015 = 0.966; IF5years = 1.479; MNiSW2015 = 20] link

Gajewicz A., Schaeublin N., Rasulev B., Hussain S., Leszczynska D., Puzyn T., Leszczynski J. (2015): Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: Hints from nano-QSAR studies, Nanotoxicology, 9, 313-325 [IF2015 = 7.913; IF5years = 8.137; MNiSW2015 = 45] link

Tantra R., Oksel C., Puzyn T., Wang J., Robinson K. N., Wang X. Z., Ma C. Y., Wilkins T. (2015): Nano(Q)SAR: Challenges, pitfalls and perspectives. Nanotoxicology 9, 636-642. [IF2015 = 7.913; IF5years = 8.137; MNiSW2015 = 45] link

Sosnowska A., Barycki M., Zaborowska M., Rybinska A., Puzyn T. (2014): Towards designing environmentally safe ionic liquids: the influence of the cation structure. Green Chemistry 16, 4749-4757 [IF2014 = 8.020; IF5years = 8.294; MNiSW2014 = 40] link

Sosnowska A., Barycki M., Jagiello K., Haranczyk M., Gajewicz A., Kawai T., Suzuki N., Puzyn T. (2014): Predicting enthalpy of vaporization for Persistent Organic Pollutants with Quantitative Structure-Property Relationship (QSPR) incorporating the influence of temperature on volatility. Atmospheric Environment 87, 10-18 [IF2014 = 3.281; IF5years = 3.780; MNiSW2014 = 35] link

Sizochenko N., Rasulev B., Gajewicz A., Kuz'min V., Puzyn T., Leszczynski J. (2014): From basic physics to mechanisms of toxicity: the "liquid drop" approach applied to develop predictive classification models for toxicity of metal oxide nanoparticles. Nanoscale 6, 13986-13993 
[IF2014 = 7.394; IF5years = 7.762; MNiSW2014 = 40] link

Kawai T., Jagiello K., Sosnowska A., Odziomek K., Gajewicz A., Handoh I. C., Puzyn T., Suzuki N. (2014): A New Metric for Long-Range Transport Potential of Chemicals. Environmental Science & Technology 48, 3245-3252 [IF2014 = 5.330; IF5years = 6.326; MNiSW2014 = 45] link

Kar S., Gajewicz A., Puzyn T., Roy K., Leszczynski J. (2014): Periodic table-based descriptors to encode cytotoxicity profile of metal oxide nanoparticles: a mechanistic QSTR approach. Ecotoxicology and Environmntal Safety 107, 162-169 
[IF2014 = 2.762; IF5years = 2.878; MNiSW2014 = 30] link

Kar S., Gajewicz A., Puzyn T., Roy K. (2014): Nano-quantitative structure-activity relationship modeling using easily computable and interpretable descriptors for uptake of magnetofluorescent engineered nanoparticles in pancreatic cancer cells. Toxicology in Vitro 28, 600-606 
[IF2014 = 2.903; IF5years = 3.047; MNiSW2014 = 30] link

Jagiello K., Sosnowska A., Walker S., Haranczyk M., Gajewicz A., Kawai T., Suzuki N., Leszczynski J., Puzyn T. (2014): Direct QSPR: the most efficient way of predicting organic carbon/water partition coefficient (log KOC) for polyhalogenated POPs. Structural Chemistry 25, 997-1004 [IF2014 = 1.837; IF5years = 1.598; MNiSW2014 = 25] link

Golebiowski M., Sosnowska A., Puzyn T., Bogus M. I., Wieloch W., Wloka E., Stepnowski P. (2014): Application of Two-Way Hierarchical Cluster Analysis for the Identification of Similarities between the Individual Lipid Fractions of Lucilia sericata. Chemistry & Biodiversity 11, 733-748 
[IF2014 = 1.515; IF5years = 1.686; MNiSW2014 = 25] link

Bielinska-Waz D., Waz P., Jagiello K., Puzyn T. (2014): Spectral density distribution moments as novel descriptors for QSAR/QSPR. Structural Chemistry 25, 29-35 [IF2014 = 1.837; IF5years = 1.596; MNiSW2014 = 25] link

Toropova A. P., Toropov A. A., Puzyn T., Benfenati E., Leszczynska D., Leszczynski J. (2013): Optimal descriptor as a translator of eclectic information into the prediction of thermal conductivity of micro-electro-mechanical systems. Journal of Mathematical Chemistry 51, 2230-2237 [IF2013 = 1.270; IF5years = 1.195; MNiSW2013 = 25; Cyt. = 8] 

Toropov A. A., Toropova A. P., Puzyn T., Benfenati E., Gini G., Leszczynska D., Leszczynski J. (2013): QSAR as a random event: Modeling of nanoparticles uptake in PaCa2 cancer cells. Chemosphere 92, 31-37 [IF2013 = 3.137; IF5years = 3.634; MNiSW2013 = 40; Cyt. = 50] link

Odziomek K., Gajewicz A., Haranczyk M., Puzyn T. (2013): Reliability of environmental fate modeling results for POPs based on various methods of determining the air/water partition coefficient (log KAW). Atmospheric Environment 73, 177-184 
[IF2013 = 3.110; IF5years = 3.787; MNiSW2013 = 40; Cyt. = 5] link

Lubinski L., Urbaszek P., Gajewicz A., Cronin M. T. D., Enoch S. J., Madden J. C., Leszczynska D., Leszczynski J., Puzyn T. (2013):
Evaluation criteria for the quality of published experimental data on nanomaterials and their usefulness for QSAR modelling. SAR and QSAR
in Environmental Research 24, 995-1008 [IF2013 = 1.667; IF5years = 1.702; MNiSW2013 = 25; Cyt. = 14] link

Bielinska-Waz D., Waz P., Clark T., Puzyn T., Peplowski L., Nowak W. (2013): Statistical properties of spectra of chloronaphthalenes.
Journal of Mathematical Chemistry 51, 857-867 [IF2013 = 1.226; IF5years = 1.166; MNiSW2013 = 25; Cyt. = 4] link

Toropov A. A., Toropova A. P., Benfenati E., Gini G., Puzyn T., Leszczynska D., Leszczynski J. (2012): Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli. Chemosphere 89, 1098-1102 
[IF2012 = 3.137; IF5years = 3.634; MNiSW2012 = 40] link

Skwarzec B., Kabat K., Puzyn T., Astel A. (2012): Inflow of polonium, uranium and plutonium radionuclides in Odra River catchment area assessment by environmetric expertise. Journal of Radioanalytical and Nuclear Chemistry 292, 519-529 
[IF2012 = 1.467; IF5years = 1.110; MNiSW2012 = 20] link

Haranczyk M., Urbaszek P., Ng E. G., Puzyn T. (2012): Combinatorial x Computational x Cheminformatics (C-3) Approach to Characterization of Congeneric Libraries of Organic Pollutants. Journal of Chemical Information and Modeling 52, 2902-2909 
[IF2012 = 4.304; IF5years = 4.067; MNiSW2012 = 40] link

Gajewicz A., Rasulev B., Dinadayalane T. C., Urbaszek P., Puzyn T., Leszczynska D., Leszczynski J. (2012): Advancing risk assessment of engineered nanomaterials: Application of computational approaches. Advanced Drug Delivery Reviews 64, 1663-1693 
[IF2012 = 12.888; IF5years = 15.431; MNiSW2012 = 50] link

Gajewicz A., Puzyn T., Rasulev B., Leszczynska D., Leszczynski J. (2011): Metal oxide nanoparticles: Size-dependence of quantum-mechanical properties. Nanosci. Nanotech. Asia 1, 53-58. [New journal; MNiSW = 2] link

Puzyn T., Haranczyk M., Suzuki N., Sakurai T. (2011): Estimating persistence of brominated and chlorinated organic pollutants in air, water, soil, and sediments with the QSPR-based classification scheme. Molecular Diversity 15, 173-188
[IF2011 = 3.153; IF5years = 3.236; MNiSW2011 = 40] link

Puzyn T, Gajewicz A, Rybacka A, Haranczyk M (2011): Global vs. local QSPR models for persistent organic pollutants: balancing between predictivity and economy. Struct. Chem. 22 (4), 795-804 [IF2011 = 1,846, IF 5 years = 1.392, MNiSW = 25; Open access] link

Puzyn T., Mostrag-Szlichtyng A., Gajewicz A., Skrzyński M. & Worth A. (2011): Investigating the influence of data splitting on the predictive ability of QSAR/QSPR models. Structural Chemistry, 22(4), 873-884 [IF2011 = 1,846, IF5 years = lacking, MNiSW = 25, Open access]. link

Puzyn T., Rasulev B., Gajewicz A., Hu X., Dasari T., Michalkova A., Hwang H-M., Toropov A., Leszczynska D. and Leszczynski J (2011): Using nano-QSAR to predict the CITtoxiCITy of metal oxide nanoparticles. Nature Nanotechnology, Nature Nanotechnlol. 6, 175-178
[IF2011 = 27.270; IF5years = 33.781, MNiSW = 50] link

Puzyn T (2011): On the replacement of empirical parameters in multimedia mass balance models with QSPR data. J. Hazard. Mater. 192 (3), 970-977. [IF2011 = 4.173, IF 5 years = 4.553, MNiSW = 45] link

Gołębiowski M., Siedlecka E, Paszkiewicz M., Brzozowski K., Stepnowski P. (2011): Perfluorocarboxylic acids in cell growth media and technologically treated waters: Determination with GC and GC–MS. Journal of Pharmaceutical and Biomedical Analysis 54, 577–581. link

Gołębiowski M., Boguś M.I., Paszkiewicz M. , Stepnowski P. (2011): Cuticular lipids of insects as a potential biofungicides: methods of lipids composition analysis. Anal. Bioanal. Chem. 399, 3177-3191. link

Haliński Ł. P, Paszkiewicz M., Gołębiowski M., Stepnowski P. (2011): The chemical composition of cuticular waxes from leaves of the gboma eggplant (Solanum macrocarpon L.). J. Food Compos. Anal. 25, 74-78. link

Gołębiowski M., Paszkiewicz M., Grubba A., Gąsiewska D., Boguś M.I., Włóka E., Wieloch W., Stepnowski P. (2011): Cuticular and internal n-alkane composition of Lucilia sericata larvae, pupae, male and female imagines; application of HPLC-LLSD and GC/MS-SIM. Bull. Entomol. Res. 102, 453-460. link