Advanced Search
Display options
Filter resources
Text Availability
Article type
Publication date
Species
Language
Sex
Age
Showing 157 to 165 of 165 entries
Sorted by: Best Match Show Resources per page
Structure-based classification of EGFR mutations informs inhibitor selection for lung cancer therapy.

Cancer cell

Yenerall P, Kittler R, Minna J.
PMID: 34752753
Cancer Cell. 2021 Nov 08;39(11):1455-1457. doi: 10.1016/j.ccell.2021.10.012. Epub 2021 Nov 08.

EGFR oncogenic mutations predict sensitivity to EGFR inhibitors in NSCLC, but less is known about EGFR "variants of unknown significance." Using preclinical models, 3D structure analyses, and patient response data, Robichaux et al. show in Nature that mutations in...

Cite
Yenerall P, Kittler R, Minna J. Structure-based classification of EGFR mutations informs inhibitor selection for lung cancer therapy. Cancer Cell. 2021;39(11):1455-1457doi: 10.1016/j.ccell.2021.10.012.
Yenerall, P., Kittler, R., & Minna, J. (2021). Structure-based classification of EGFR mutations informs inhibitor selection for lung cancer therapy. Cancer cell, 39(11), 1455-1457. https://doi.org/10.1016/j.ccell.2021.10.012
Yenerall, Paul, et al. "Structure-based classification of EGFR mutations informs inhibitor selection for lung cancer therapy." Cancer cell vol. 39,11 (2021): 1455-1457. doi: https://doi.org/10.1016/j.ccell.2021.10.012
Yenerall P, Kittler R, Minna J. Structure-based classification of EGFR mutations informs inhibitor selection for lung cancer therapy. Cancer Cell. 2021 Nov 08;39(11):1455-1457. doi: 10.1016/j.ccell.2021.10.012. Epub 2021 Nov 08. PMID: 34752753.
Copy Download .nbib Format: NLM
Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context.

Scientific data

Rotemberg V, Kurtansky N, Betz-Stablein B, Caffery L, Chousakos E, Codella N, Combalia M, Dusza S, Guitera P, Gutman D, Halpern A, Helba B, Kittler H, Kose K, Langer S, Lioprys K, Malvehy J, Musthaq S, Nanda J, Reiter O, Shih G, Stratigos A, Tschandl P, Weber J, Soyer HP.
PMID: 33674616
Sci Data. 2021 Mar 05;8(1):81. doi: 10.1038/s41597-021-00865-3.

No abstract available.

Cite
Rotemberg V, Kurtansky N, Betz-Stablein B, et al. Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Sci Data. 2021;8(1):81doi: 10.1038/s41597-021-00865-3.
Rotemberg, V., Kurtansky, N., Betz-Stablein, B., Caffery, L., Chousakos, E., Codella, N., Combalia, M., Dusza, S., Guitera, P., Gutman, D., Halpern, A., Helba, B., Kittler, H., Kose, K., Langer, S., Lioprys, K., Malvehy, J., Musthaq, S., Nanda, J., Reiter, O., Shih, G., Stratigos, A., Tschandl, P., Weber, J., & Soyer, H. P. (2021). Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Scientific data, 8(1), 81. https://doi.org/10.1038/s41597-021-00865-3
Rotemberg, Veronica, et al. "Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context." Scientific data vol. 8,1 (2021): 81. doi: https://doi.org/10.1038/s41597-021-00865-3
Rotemberg V, Kurtansky N, Betz-Stablein B, Caffery L, Chousakos E, Codella N, Combalia M, Dusza S, Guitera P, Gutman D, Halpern A, Helba B, Kittler H, Kose K, Langer S, Lioprys K, Malvehy J, Musthaq S, Nanda J, Reiter O, Shih G, Stratigos A, Tschandl P, Weber J, Soyer HP. Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Sci Data. 2021 Mar 05;8(1):81. doi: 10.1038/s41597-021-00865-3. PMID: 33674616; PMCID: PMC7935940.
Copy Download .nbib Format: NLM
Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database.

The Australasian journal of dermatology

Jimenez Balcells C, Hay J, Keir J, Rosendahl N, Coetzer-Botha M, Wilson T, Clark S, Baade A, Becker C, Bookallil L, Clifopoulos C, Dicker T, Denby MP, Duthie D, Elliott C, Fishburn P, Foley M, Franck M, Giam I, Gordillo P, Lilleyman A, Macauley R, Maher J, McPhee E, Reid M, Shirlaw B, Siggs G, Spark R, Stretch J, van den Heever K, van Rensburg T, Watson C, Kittler H, Rosendahl C.
PMID: 34423846
Australas J Dermatol. 2021 Nov;62(4):496-503. doi: 10.1111/ajd.13705. Epub 2021 Aug 23.

BACKGROUND AND OBJECTIVE: Most melanomas (including melanomas in situ), in Australasia, are treated by general practitioners (GPs). Previously undescribed, the characteristics of a series of melanomas treated by multiple GPs are examined.PATIENTS AND METHODS: Six hundred and thirty-seven melanomas...

Cite
Jimenez Balcells C, Hay J, Keir J, et al. Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database. Australas J Dermatol. 2021;62(4):496-503doi: 10.1111/ajd.13705.
Jimenez Balcells, C., Hay, J., Keir, J., Rosendahl, N., Coetzer-Botha, M., Wilson, T., Clark, S., Baade, A., Becker, C., Bookallil, L., Clifopoulos, C., Dicker, T., Denby, M. P., Duthie, D., Elliott, C., Fishburn, P., Foley, M., Franck, M., Giam, I., Gordillo, P., Lilleyman, A., Macauley, R., Maher, J., McPhee, E., Reid, M., Shirlaw, B., Siggs, G., Spark, R., Stretch, J., van den Heever, K., van Rensburg, T., Watson, C., Kittler, H., & Rosendahl, C. (2021). Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database. The Australasian journal of dermatology, 62(4), 496-503. https://doi.org/10.1111/ajd.13705
Jimenez Balcells, Clara, et al. "Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database." The Australasian journal of dermatology vol. 62,4 (2021): 496-503. doi: https://doi.org/10.1111/ajd.13705
Jimenez Balcells C, Hay J, Keir J, Rosendahl N, Coetzer-Botha M, Wilson T, Clark S, Baade A, Becker C, Bookallil L, Clifopoulos C, Dicker T, Denby MP, Duthie D, Elliott C, Fishburn P, Foley M, Franck M, Giam I, Gordillo P, Lilleyman A, Macauley R, Maher J, McPhee E, Reid M, Shirlaw B, Siggs G, Spark R, Stretch J, van den Heever K, van Rensburg T, Watson C, Kittler H, Rosendahl C. Characteristics of 637 melanomas documented by 27 general practitioners on the Skin Cancer Audit Research Database. Australas J Dermatol. 2021 Nov;62(4):496-503. doi: 10.1111/ajd.13705. Epub 2021 Aug 23. PMID: 34423846.
Copy Download .nbib Format: NLM
Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With .

Frontiers in bioengineering and biotechnology

Kopp J, Kittler S, Slouka C, Herwig C, Spadiut O, Wurm DJ.
PMID: 33240864
Front Bioeng Biotechnol. 2020 Nov 10;8:573607. doi: 10.3389/fbioe.2020.573607. eCollection 2020.

Recombinant protein production with

Cite
Kopp J, Kittler S, Slouka C, et al. Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With . Front Bioeng Biotechnol. 2020;8:573607doi: 10.3389/fbioe.2020.573607.
Kopp, J., Kittler, S., Slouka, C., Herwig, C., Spadiut, O., & Wurm, D. J. (2020). Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With . Frontiers in bioengineering and biotechnology, 8573607. https://doi.org/10.3389/fbioe.2020.573607
Kopp, Julian, et al. "Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With ." Frontiers in bioengineering and biotechnology vol. 8 (2020): 573607. doi: https://doi.org/10.3389/fbioe.2020.573607
Kopp J, Kittler S, Slouka C, Herwig C, Spadiut O, Wurm DJ. Repetitive Fed-Batch: A Promising Process Mode for Biomanufacturing With . Front Bioeng Biotechnol. 2020 Nov 10;8:573607. doi: 10.3389/fbioe.2020.573607. eCollection 2020. PMID: 33240864; PMCID: PMC7683717.
Copy Download .nbib Format: NLM
Relaxed Block-Diagonal Dictionary Pair Learning With Locality Constraint for Image Recognition.

IEEE transactions on neural networks and learning systems

Chen Z, Wu XJ, Kittler J.
PMID: 33764879
IEEE Trans Neural Netw Learn Syst. 2021 Mar 25; doi: 10.1109/TNNLS.2021.3053941. Epub 2021 Mar 25.

We propose a novel structured analysis-synthesis dictionary pair learning method for efficient representation and image classification, referred to as relaxed block-diagonal dictionary pair learning with a locality constraint (RBD-DPL). RBD-DPL aims to learn relaxed block-diagonal representations of the input...

Cite
Chen Z, Wu XJ, Kittler J. Relaxed Block-Diagonal Dictionary Pair Learning With Locality Constraint for Image Recognition. IEEE Trans Neural Netw Learn Syst. 2021;doi: 10.1109/TNNLS.2021.3053941.
Chen, Z., Wu, X. J., & Kittler, J. (2021). Relaxed Block-Diagonal Dictionary Pair Learning With Locality Constraint for Image Recognition. IEEE transactions on neural networks and learning systems, . https://doi.org/10.1109/TNNLS.2021.3053941
Chen, Zhe, et al. "Relaxed Block-Diagonal Dictionary Pair Learning With Locality Constraint for Image Recognition." IEEE transactions on neural networks and learning systems vol. (2021). doi: https://doi.org/10.1109/TNNLS.2021.3053941
Chen Z, Wu XJ, Kittler J. Relaxed Block-Diagonal Dictionary Pair Learning With Locality Constraint for Image Recognition. IEEE Trans Neural Netw Learn Syst. 2021 Mar 25; doi: 10.1109/TNNLS.2021.3053941. Epub 2021 Mar 25. PMID: 33764879.
Copy Download .nbib Format: NLM
Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER.

Clinical cancer research : an official journal of the American Association for Cancer Research

Servetto A, Kollipara R, Formisano L, Lin CC, Lee KM, Sudhan DR, Gonzalez-Ericsson PI, Chatterjee S, Guerrero-Zotano A, Mendiratta S, Akamatsu H, James N, Bianco R, Hanker AB, Kittler R, Arteaga CL.
PMID: 34011560
Clin Cancer Res. 2021 Aug 01;27(15):4379-4396. doi: 10.1158/1078-0432.CCR-20-3905. Epub 2021 May 19.

PURPOSE: FGFR1 overexpression has been associated with endocrine resistance in EREXPERIMENTAL DESIGN: Tumors from patients treated with letrozole were subjected to Ki67 and FGFR1 IHC. MCF7 cells were transduced with FGFR1(SP-)(NLS) to promote nuclear FGFR1 overexpression. FGFR1 genomic activity...

Cite
Servetto A, Kollipara R, Formisano L, et al. Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER. Clin Cancer Res. 2021;27(15):4379-4396doi: 10.1158/1078-0432.CCR-20-3905.
Servetto, A., Kollipara, R., Formisano, L., Lin, C. C., Lee, K. M., Sudhan, D. R., Gonzalez-Ericsson, P. I., Chatterjee, S., Guerrero-Zotano, A., Mendiratta, S., Akamatsu, H., James, N., Bianco, R., Hanker, A. B., Kittler, R., & Arteaga, C. L. (2021). Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER. Clinical cancer research : an official journal of the American Association for Cancer Research, 27(15), 4379-4396. https://doi.org/10.1158/1078-0432.CCR-20-3905
Servetto, Alberto, et al. "Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER." Clinical cancer research : an official journal of the American Association for Cancer Research vol. 27,15 (2021): 4379-4396. doi: https://doi.org/10.1158/1078-0432.CCR-20-3905
Servetto A, Kollipara R, Formisano L, Lin CC, Lee KM, Sudhan DR, Gonzalez-Ericsson PI, Chatterjee S, Guerrero-Zotano A, Mendiratta S, Akamatsu H, James N, Bianco R, Hanker AB, Kittler R, Arteaga CL. Nuclear FGFR1 Regulates Gene Transcription and Promotes Antiestrogen Resistance in ER. Clin Cancer Res. 2021 Aug 01;27(15):4379-4396. doi: 10.1158/1078-0432.CCR-20-3905. Epub 2021 May 19. PMID: 34011560; PMCID: PMC8338892.
Copy Download .nbib Format: NLM
Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context.

Scientific data

Rotemberg V, Kurtansky N, Betz-Stablein B, Caffery L, Chousakos E, Codella N, Combalia M, Dusza S, Guitera P, Gutman D, Halpern A, Helba B, Kittler H, Kose K, Langer S, Lioprys K, Malvehy J, Musthaq S, Nanda J, Reiter O, Shih G, Stratigos A, Tschandl P, Weber J, Soyer HP.
PMID: 33727560
Sci Data. 2021 Mar 16;8(1):88. doi: 10.1038/s41597-021-00879-x.

No abstract available.

Cite
Rotemberg V, Kurtansky N, Betz-Stablein B, et al. Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Sci Data. 2021;8(1):88doi: 10.1038/s41597-021-00879-x.
Rotemberg, V., Kurtansky, N., Betz-Stablein, B., Caffery, L., Chousakos, E., Codella, N., Combalia, M., Dusza, S., Guitera, P., Gutman, D., Halpern, A., Helba, B., Kittler, H., Kose, K., Langer, S., Lioprys, K., Malvehy, J., Musthaq, S., Nanda, J., Reiter, O., Shih, G., Stratigos, A., Tschandl, P., Weber, J., & Soyer, H. P. (2021). Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Scientific data, 8(1), 88. https://doi.org/10.1038/s41597-021-00879-x
Rotemberg, Veronica, et al. "Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context." Scientific data vol. 8,1 (2021): 88. doi: https://doi.org/10.1038/s41597-021-00879-x
Rotemberg V, Kurtansky N, Betz-Stablein B, Caffery L, Chousakos E, Codella N, Combalia M, Dusza S, Guitera P, Gutman D, Halpern A, Helba B, Kittler H, Kose K, Langer S, Lioprys K, Malvehy J, Musthaq S, Nanda J, Reiter O, Shih G, Stratigos A, Tschandl P, Weber J, Soyer HP. Publisher Correction: Author Correction: A patient-centric dataset of images and metadata for identifying melanomas using clinical context. Sci Data. 2021 Mar 16;8(1):88. doi: 10.1038/s41597-021-00879-x. PMID: 33727560; PMCID: PMC7966738.
Copy Download .nbib Format: NLM
Resveratrol Alleviates Acute .

Microorganisms

Heimesaat MM, Mousavi S, Escher U, Lobo de Sá FD, Peh E, Schulzke JD, Kittler S, Bücker R, Bereswill S.
PMID: 33255723
Microorganisms. 2020 Nov 25;8(12). doi: 10.3390/microorganisms8121858.

The polyphenolic compound resveratrol has been shown to exert health-beneficial properties. Given globally emerging

Cite
Heimesaat MM, Mousavi S, Escher U, et al. Resveratrol Alleviates Acute . Microorganisms. 2020;8(12)doi: 10.3390/microorganisms8121858.
Heimesaat, M. M., Mousavi, S., Escher, U., Lobo de Sá, F. D., Peh, E., Schulzke, J. D., Kittler, S., Bücker, R., & Bereswill, S. (2020). Resveratrol Alleviates Acute . Microorganisms, 8(12), . https://doi.org/10.3390/microorganisms8121858
Heimesaat, Markus M, et al. "Resveratrol Alleviates Acute ." Microorganisms vol. 8,12 (2020). doi: https://doi.org/10.3390/microorganisms8121858
Heimesaat MM, Mousavi S, Escher U, Lobo de Sá FD, Peh E, Schulzke JD, Kittler S, Bücker R, Bereswill S. Resveratrol Alleviates Acute . Microorganisms. 2020 Nov 25;8(12). doi: 10.3390/microorganisms8121858. PMID: 33255723; PMCID: PMC7760181.
Copy Download .nbib Format: NLM
Lentiviral-Driven Discovery of Cancer Drug Resistance Mutations.

Cancer research

Yenerall P, Kollipara RK, Avila K, Peyton M, Eide CA, Bottomly D, McWeeney SK, Liu Y, Westover KD, Druker BJ, Minna JD, Kittler R.
PMID: 34301758
Cancer Res. 2021 Sep 15;81(18):4685-4695. doi: 10.1158/0008-5472.CAN-21-1153. Epub 2021 Jul 23.

Identifying resistance mutations in a drug target provides crucial information. Lentiviral transduction creates multiple types of mutations due to the error-prone nature of the HIV-1 reverse transcriptase (RT). Here we optimized and leveraged this property to identify drug resistance...

Cite
Yenerall P, Kollipara RK, Avila K, et al. Lentiviral-Driven Discovery of Cancer Drug Resistance Mutations. Cancer Res. 2021;81(18):4685-4695doi: 10.1158/0008-5472.CAN-21-1153.
Yenerall, P., Kollipara, R. K., Avila, K., Peyton, M., Eide, C. A., Bottomly, D., McWeeney, S. K., Liu, Y., Westover, K. D., Druker, B. J., Minna, J. D., & Kittler, R. (2021). Lentiviral-Driven Discovery of Cancer Drug Resistance Mutations. Cancer research, 81(18), 4685-4695. https://doi.org/10.1158/0008-5472.CAN-21-1153
Yenerall, Paul, et al. "Lentiviral-Driven Discovery of Cancer Drug Resistance Mutations." Cancer research vol. 81,18 (2021): 4685-4695. doi: https://doi.org/10.1158/0008-5472.CAN-21-1153
Yenerall P, Kollipara RK, Avila K, Peyton M, Eide CA, Bottomly D, McWeeney SK, Liu Y, Westover KD, Druker BJ, Minna JD, Kittler R. Lentiviral-Driven Discovery of Cancer Drug Resistance Mutations. Cancer Res. 2021 Sep 15;81(18):4685-4695. doi: 10.1158/0008-5472.CAN-21-1153. Epub 2021 Jul 23. PMID: 34301758; PMCID: PMC8448967.
Copy Download .nbib Format: NLM
Showing 157 to 165 of 165 entries