Results 1 to 10 of about 5,026,987 (343)

GreedyMini: generating low-density DNA minimizers. [PDF]

Bioinformatics
Golan S, Tziony I, Kraus M, Orenstein Y, Shur A.   +4 more
europepmc   +1 more source

Computer and Information Science, Vol. 1, No. 2, May 2008, all in one file

, 2008
Editor CIS
openalex   +2 more sources

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

Correction: Deep learning-based text generation for plant phenotyping and precision agriculture. [PDF]

Front Plant Sci
Zhu L, Tang L, Ren S.
europepmc   +1 more source

Computer and Information Science, Vol. 2, No. 2, May 2009, all in one file, Part A

, 2009
Editor CIS
openalex   +1 more source

TRPM8 levels determine tumor vulnerability to channel agonists

Molecular Oncology, EarlyView.
TRPM8 is a Ca2+ permissive channel. Regardless of the amount of its transcript, high levels of TRPM8 protein mark different tumors, including prostate, breast, colorectal, and lung carcinomas. Targeting TRPM8 with channel agonists stimulates inward calcium currents followed by emptying of cytosolic Ca2+ stores in cancer cells.
Alessandro Alaimo, Francesco Giuseppe Carbone, Kristi Buzo, Nicole Annesi, Sacha Genovesi, Annalisa Lorenzato, Karen Widmann, Michela Libergoli, Elisa Marmocchi, Giovanni Bertalot, Alberto Brolese, Mauro Giulio Papotti, Luca Molinaro, Orazio Caffo, Mattia Barbareschi, Alberto Bardelli, Alessandro Romanel, Sabrina Arena, Andrea Lunardi   +18 more
wiley   +1 more source

The anticancer effect of the HDAC inhibitor belinostat is enhanced by inhibitors of Bcl‐xL or Mcl‐1 in ovarian cancer

Molecular Oncology, EarlyView.
The pan‐HDAC inhibitor belinostat increases the expression of the pro‐apoptotic proteins Bim, Puma, and Noxa and induces apoptosis in ovarian cancer cell lines and patient‐derived tumor organoids when used at high concentrations. Moreover, inhibiting the anti‐apoptotic proteins Bcl‐xL or Mcl‐1 sensitizes these preclinical models to the cytotoxic effect
Cécilia Thomine, Sterenn Guillemot, Louis‐Bastien Weiswald, Romane Florent, Edwige Abeilard, Florence Giffard, Emilie Brotin, Mélanie Briand, Enora Dolivet, Laurent Poulain, Marie Villedieu   +10 more
wiley   +1 more source

Correction: Zhang et al. Discovery of a Ruthenium Complex for the Theranosis of Glioma through Targeting the Mitochondrial DNA with Bioinformatic Methods. <i>Int. J. Mol. Sci.</i> 2019, <i>20</i>, 4643. [PDF]

Int J Mol Sci
Zhang L, Fu C, Li J, Zhao Z, Hou Y, Zhou W, Fu A.   +6 more
europepmc   +1 more source

Computer and Information Science, Vol. 2, No. 3, August 2009, all in one file, Part A

, 2009
CIS Editor
openalex   +2 more sources

Systematic profiling of cancer‐fibroblast interactions reveals drug combinations in ovarian cancer

Molecular Oncology, EarlyView.
Fibroblasts, cells in the tumor environment, support ovarian cancer cell growth and alter morphology and drug response. We used fibroblast and cancer cell co‐culture models to test 528 drugs and discovered new drugs for combination treatment. We showed that adding Vorinostat or Birinapant to standard chemotherapy may improve drug response, suggesting ...
Greta Gudoityte, Osheen Sharma, Laura Leuenberger, Emelie Wallin, Josefin Fernebro, Päivi Östling, Rebecka Bergström, Johan Lindberg, Ulrika Joneborg, Olli Kallioniemi, Brinton Seashore‐Ludlow   +10 more
wiley   +1 more source