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209
datasets available to search
ShareScore release 0.9.0
Dataset results
209 results for “ABL”
Effect of MPC309 (AR-targeting Multivalent Peptoid Conjugate) treatment on gene expression in LNCaP-ABL cells (castration-resistant prostate cancer cell line) in comparison to Vehicle control and anot
GEO Series GSE236088. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
The effect of Abl kinases,or Ponatinib challenging on breast cancer cells' global transcriptome
GEO Series GSE95079. Homo sapiens. 8 samples. Type: Expression profiling by high throughput sequencing.
Effects of Cardiac Glycosides on RNA Expression in Prostate Cancer LNCaP-abl Cells
GEO Series GSE35126. Homo sapiens. 18 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of acute mitochondrial pyruvate carrier inhibition using UK5099 in ABL prostate cancer cells
GEO Series GSE114708. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing.
Effect of MPC309 (AR-targeting Multivalent Peptoid Conjugate) treatment on gene expression in LNCaP-ABL cells (castration-resistant prostate cancer cell line) in comparison to Vehicle control and anot
GEO Series GSE236286. Homo sapiens. 10 samples. Type: Expression profiling by high throughput sequencing.
Comparative analysis of BCR-ABL tyrosine kinase inhibitors in BCR-ABL positive K562 cells
GEO Series GSE2810. Homo sapiens. 10 samples. Type: Expression profiling by array.
The long non-coding NEAT1 is a DNp63 target gene able to modulate epidermal differentiation [RNA-seq]
GEO Series GSE205960. Homo sapiens. 9 samples. Type: Expression profiling by high throughput sequencing.
Synergism between IL7R and CXCR4 drives BCR-ABL induced transformation in Philadelphia chromosome-positive acute lymphoblastic leukemia
GEO Series GSE150784. Mus musculus. 12 samples. Type: Expression profiling by high throughput sequencing.
Antidepressants affect gut microbiota and Ruminococcus flavefaciens is able to abolish their effects on depressive-like behavior
GEO Series GSE129359. Mus musculus. 24 samples. Type: Expression profiling by high throughput sequencing.
Combined targeting of GPX4 and BCR-ABL tyrosine kinase selectively compromises BCR-ABL+ leukemia stem cells
GEO Series GSE276122. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
E2F1 transcription factor knockdown effect on gene expression in LNCaP-abl cells
GEO Series GSE56331. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Global gene expression changes in patient-derived CML cell line K562 after short- and long-term BCR-ABL kinase inhibition.
GEO Series GSE51083. Homo sapiens. 12 samples. Type: Expression profiling by array.
Leukaemia Exposure Alters the Transcriptional Profile and Function of BCR-ABL Negative Macrophages in the Bone Marrow Niche
GEO Series GSE204978. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profiling of murine BCR-ABL+ CDK6-wt and CDK6-KO cells
GEO Series GSE156966. Mus musculus. 8 samples. Type: Expression profiling by high throughput sequencing; Genome binding/occupancy profiling by high throughput sequencing.
The differences of Bcr-abl+ tumor stromal cell gene expression between wild type B6 mice and Sipa1 knock out mice
GEO Series GSE108002. Mus musculus. 4 samples. Type: Expression profiling by array.
Data set to train a natural language classifier able to differentiate between 15 topics relevant to biodiversity informatics
<p><strong>Scope and size</strong><br> This data set is used to train a natural language processing classifier. The classifier shall be able to differentiate between 15 topics relevant to biodiversity informatics. The list of relevant topics was adapted from Searls (2012).</p> <p>The data set was split into training data, testing data (for tweaking and unit-testing the classifier) and validation data. Each data set is stored as PDF files in a separate directory.</p> <ul> <li>Training data (5494 pages)</li> <li>Test data (977 pages)</li> <li>Validation data (215 pages)</li> </ul> <p><strong>Data sources and licenses</strong><br> Details about the licenses for each data set can be found in the corresponding directories.</p> <ul> <li>Training data was compiled from MIT OpenCourseWare resources provided by MIT under a Creative Commons BY-NC-SA License.</li> <li>Testing data was compiled from MIT OpenCourseWare exams, provided by MIT under a Creative Commons License BY-NC-SA.</li> <li>Validation data was compiled from Wikipedia, provided under a Creative Commons License by Wikipedia editors and contributors.</li> </ul> <p><strong>Topic references</strong><br> Each topic references one or more MIT OpenCourseWare courses:</p> <ul> <li>Algorithms (Demaine, and Devadas, 2011)</li> <li>Artificial Intelligence (Winston, 2010)</li> <li>Building Dynamic Websites (Abelson, and Greenspun, 2003)</li> <li>Computational Biology (Kellis, 2015)</li> <li>Computer Graphics (Matusik, and Durand, 2012)</li> <li>Computer Science and Programming (Bell, Grimson, and Guttag, 2016)</li> <li>Databases (Madden, Morris, Stonebraker, and Curino, 2010)</li> <li>Data Structures (Demaine, 2012)</li> <li>Digital Image Processing (Clifford, Fisher, Greenberg, and Wells, 2007; Golland, 2005)</li> <li>Machine Learning (Singh, Jaakkola, and Mohammad, 2006)</li> <li>Machine Structures (Morris, and Madden, 2009)</li> <li>Natural Language Processing (Berwick, 2003; Collins, and Barzilay, 2005)</li> <li>Parallel Computing (Edelman, 2011)</li> <li>Software Engineering (Jackson, and Devadas, 2005)</li> <li>Structure and Interpretation of Computer Programs (Miller, and Goldman, 2016).</li> </ul> <p><strong>References</strong></p> <p>Harold Abelson, and Philip Greenspun. 6.171 Software Engineering for Web Applications. Fall 2003. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Ana Bell, Eric Grimson, and John Guttag. 6.0001 Introduction to Computer Science and Programming in Python. Fall 2016. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Robert Berwick. 6.863J Natural Language and the Computer Representation of Knowledge. Spring 2003. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Gari Clifford, John Fisher, Julie Greenberg, and William Wells. HST.582J Biomedical Signal and Image Processing. Spring 2007. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Michael Collins, and Regina Barzilay. 6.864 Advanced Natural Language Processing. Fall 2005. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Erik Demaine. 6.851 Advanced Data Structures. Spring 2012. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Erik Demaine, and Srini Devadas. 6.006 Introduction to Algorithms. Fall 2011. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Alan Edelman. 18.337J Parallel Computing. Fall 2011. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Polina Golland. 6.881 Representation and Modeling for Image Analysis. Spring 2005. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Daniel Jackson, and Srini Devadas. 6.170 Laboratory in Software Engineering. Fall 2005. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Manolis Kellis. 6.047 Computational Biology. Fall 2015. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Robert Miller, and Max Goldman. 6.005 Software Construction. Spring 2016. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Samuel Madden, Robert Morris, Michael Stonebraker, and Carlo Curino. 6.830 Database Systems. Fall 2010. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Wojciech Matusik, and Frédo Durand. 6.837 Computer Graphics. Fall 2012. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Morris, Robert, and Madden, Samuel. 6.033 Computer System Engineering. Spring 2009. Massachusetts Institute of Technology: MIT OpenCourseWare, http://hdl.handle.net/1721.1/118791. License: Creative Commons BY-NC-SA.</p> <p>David B. Searls. An online bioinformatics curriculum. 2012. PLoS computational biology, 8(9), p.e1002632.</p> <p>Rohit Singh, Tommi Jaakkola, and Ali Mohammad. 6.867 Machine Learning. Fall 2006. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p>Patrick Winston. 6.034 Artificial Intelligence. Fall 2010. Massachusetts Institute of Technology: MIT OpenCourseWare, https://ocw.mit.edu. License: Creative Commons BY-NC-SA.</p> <p> </p>
Front-line Nilotinib Treatment of BCR-ABL+ Chronic Myeloid Leukaemia in Chronic Phase
ClinicalTrials.gov study NCT01699217. IPD Sharing: NO. Countries: 1. Publications: 0.
Low-Intensity Chemotherapy, Ponatinib and Blinatumomab in Treating Patients With Philadelphia Chromosome-Positive and/or BCR-ABL Positive Acute Lymphoblastic Leukemia
ClinicalTrials.gov study NCT03147612. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Is the RAPDx Pupillograph Able to Distinguish Between Glaucoma Subjects and Healthy Subjects?
ClinicalTrials.gov study NCT02526693. IPD Sharing: NO. Countries: 0. Publications: 0.
Safety and Efficacy of Asciminib in Pediatrics and Young Adults With Relapse/Refractory (r/r) Philadelphia Positive (Ph+) or ABL-class Ph-like Acute Lymphoblastic Leukemia (ALL)
ClinicalTrials.gov study NCT07387926. IPD Sharing: YES. Countries: 0. Publications: 0.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.