[1] Agostinis, P., Berg, K., Cengel, K.A., Foster, T.H., Girotti, A.W., Gollnick, S.O., Hahn, S.M., Hamblin, M.R., Juzeniene, A., Kessel, D., Korbelik, M., Moan, J., Mroz, P., Nowis, D., Piette, J., Wilson, B.C., Golab, J., Photodynamic therapy of cancer: an update. CA Cancer J. Clin., 250–281, 2011.
Biodistribution of haematoporphyrin analogues in a lung carcinoma model
[6] Tronconi, W., Colombo, A., Decesare, M., Marchesini, R., Woodburn, K.W., Reiss, J.A., Phillips, D.R., Zunino, F., Biodistribution of haematoporphyrin analogues in a lung carcinoma model. Cancer Lett. 88 (1995), 41–48.
A cell-permeable, activity-based probe for protein and lipid kinases
[7] Yee, M., Fas, S.C., Stohlmeyer, M., Wandless, T.J., Cimprich, K.A., A cell-permeable, activity-based probe for protein and lipid kinases. J. Biol. Chem. 280 (2005), 29053–29059.
Pyrromethene dialkynyl borane complexes for “Cascatelle” energy transfer and protein labeling
[8] Ulrich, G., Goze, C., Guardigli, M., Roda, A., Ziessel, R., Pyrromethene dialkynyl borane complexes for “Cascatelle” energy transfer and protein labeling. Angew. Chem. Int. Ed. 44 (2005), 3694–3698.
In vitro and in vivo photocytotoxicity of boron dipyrromethene derivatives for photodynamic therapy
[14] Lim, S.H., Thivierge, C., Nowak-Sliwinska, P., Han, J., van den Bergh, H., Wagnières, G., Burgess, K., Lee, H.B., In vitro and in vivo photocytotoxicity of boron dipyrromethene derivatives for photodynamic therapy. J. Med. Chem. 53 (2010), 2865–2874.
Towards improved halogenated BODIPY photosensitizers: clues on structural designs and heavy atom substitution patterns
[17] Sanchez-Arroyo, A., Palao, E., Agarrabeitia, A.R., Ortiz, M.J., Garcia-Fresnadillo, D., Towards improved halogenated BODIPY photosensitizers: clues on structural designs and heavy atom substitution patterns. Phys. Chem. Chem. Phys. 19 (2017), 69–72.
Spectral properties of single BODIPY dyes in polystyrene microspheres and in solutions
[18] Wittmershaus, B.P., Skibicki, J.J., McLafferty, J.B., Zhang, Y.Z., Swan, S., Spectral properties of single BODIPY dyes in polystyrene microspheres and in solutions. J. Fluoresc. 11 (2001), 119–128.
Synthesis and photo-physical properties of a series of BODIPY dyes
[19] Banfi, S., Nasini, G., Zaza, S., Caruso, E., Synthesis and photo-physical properties of a series of BODIPY dyes. Tetrahedron 69 (2013), 4845–4856.
Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay
[22] Alley, M.C., Scudiero, D.A., Monks, A., Hursey, M.L., Czerwinski, M.J., Fine, D.L., Abbott, B.J., Mayo, J.G., Shoemaker, R.H., Boyd, M.R., Feasibility of drug screening with panels of human tumor cell lines using a microculture tetrazolium assay. Cancer Res. 48 (1988), 589–601.
Hypercube, Inc. 1115 NW 4th Street, Gainesville, Florida 32601, USA (windows)
[23] HyperChem (TM). v 7.03, 2002, Hypercube, Inc., 1115 NW 4th Street, Gainesville, Florida 32601, USA (windows).
(2002), vol.v 7.03
24
85009351618
DRAGON for Windows (Software for Molecular Descriptor Calculations)
Talete (windows)
[24] DRAGON for Windows (Software for Molecular Descriptor Calculations). v 5.5, 2007, Talete (windows).
(2007), vol.v 5.5
25
84885947615
QSARINS: a new software for the development, analysis and validation of QSAR MLR models
[25] Gramatica, P., Chirico, N., Papa, E., Cassani, S., Kovarich, S., QSARINS: a new software for the development, analysis and validation of QSAR MLR models. J. Comput. Chem. 34 (2013), 2121–2132.
QSARINS-Chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS
[26] Gramatica, P., Cassani, S., Chirico, N., QSARINS-Chem: Insubria datasets and new QSAR/QSPR models for environmental pollutants in QSARINS. J. Comput. Chem. 35 (2014), 1036–1044.
Real external Predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient
[27] Chirico, N., Gramatica, P., Real external Predictivity of QSAR models: how to evaluate it? Comparison of different validation criteria and proposal of using the concordance correlation coefficient. J. Chem. Inf. Model. 51 (2011), 2320–2335.
Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection
[28] Chirico, N., Gramatica, P., Real external predictivity of QSAR models. Part 2. New intercomparable thresholds for different validation criteria and the need for scatter plot inspection. J. Chem. Inf. Model. 52 (2012), 2044–2058.
The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models
[29] Tropsha, A., Gramatica, P., Gombar, V.K., The importance of being earnest: validation is the absolute essential for successful application and interpretation of QSPR models. QSAR Comb. Sci. 22 (2003), 69–77.
QSAR modeling is not “push a button and find a correlation”: a case study of toxicity of (benzo-)triazoles on algae
[30] Gramatica, P., Cassani, S., Roy, P.P., Kovarich, S., Yap, C.W., Papa, E., QSAR modeling is not “push a button and find a correlation”: a case study of toxicity of (benzo-)triazoles on algae. Mol. Inf. 31 (2012), 817–835.
Distyryl-boradiazaindacenes: facile synthesis of novel near IR emitting fluorophores
[31] Akkaya, E.U., Dost, Z., Atilgan, S., Distyryl-boradiazaindacenes: facile synthesis of novel near IR emitting fluorophores. Tetrahedron 62 (2006), 8484–8488.
Highly efficient energy transfer in subphthalocyanine-BODIPY conjugates
[32] Liu, J.Y., Yeund, H.S., Xu, W., Li, X., Ng, D.K.P., Highly efficient energy transfer in subphthalocyanine-BODIPY conjugates. Org. Lett. 10 (2008), 5421–5424.