Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Keyword
-
- Machine learning (2)
- Binding Sites (1)
- Breast cancer (1)
- Chemotherapy resistance (1)
- Cytogenetics (1)
-
- Datasets as Topic (1)
- Entropy (1)
- Gene expression signatures (1)
- Genome (1)
- Genome, Human (1)
- HeLa Cells (1)
- Hormone therapy (1)
- Human (1)
- Humans (1)
- Image processing (1)
- Information Theory (1)
- K562 Cells (1)
- Nucleotide Motifs (1)
- Oligonucleotide Array Sequence Analysis (1)
- Polymorphism (1)
- Polymorphism, Single Nucleotide (1)
- Position-Specific Scoring Matrices (1)
- Protein Binding (1)
- Radiation biodosimetry (1)
- Random forest (1)
- Reproducibility of Results (1)
- Single Nucleotide (1)
- Support vector machine (1)
- Transcription Factors (1)
Articles 1 - 5 of 5
Full-Text Articles in Life Sciences
Expedited Radiation Biodosimetry By Automated Dicentric Chromosome Identification (Adci) And Dose Estimation, Peter Rogan, Ben Shirley, Yanxin Li, Joan Knoll
Expedited Radiation Biodosimetry By Automated Dicentric Chromosome Identification (Adci) And Dose Estimation, Peter Rogan, Ben Shirley, Yanxin Li, Joan Knoll
Biochemistry Publications
Biological radiation dose can be estimated from dicentric chromosome frequencies in metaphase cells. Performing these cytogenetic dicentric chromosome assays is traditionally a manual, labor-intensive process not well suited to handle the volume of samples which may require examination in the wake of a mass casualty event. Automated Dicentric Chromosome Identifier and Dose Estimator (ADCI) software automates this process by examining sets of metaphase images using machine learning-based image processing techniques. The software selects appropriate images for analysis by removing unsuitable images, classifies each object as either a centromere-containing chromosome or non-chromosome, further distinguishes chromosomes as monocentric chromosomes (MCs) or dicentric …
Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan
Accurate Cytogenetic Biodosimetry Through Automated Dicentric Chromosome Curation And Metaphase Cell Selection, Jin Liu, Yanxin Li, Ruth Wilkins, Canadian Nuclear Laboratories, Joan H. Knoll, Peter Rogan
Biochemistry Publications
Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments. We also present image segmentation methods to rank high quality digital metaphase images and eliminate suboptimal metaphase cells. A set of chromosome morphology segmentation methods selectively filtered out FP DCs …
Predicting Outcomes Of Hormone And Chemotherapy In The Molecular Taxonomy Of Breast Cancer International Consortium (Metabric) Study By Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Katherina Baranova, Huy Q. Pham, Iman Rezaeian, Dimo Angelov, Alioune Ngom, Luis Rueda
Predicting Outcomes Of Hormone And Chemotherapy In The Molecular Taxonomy Of Breast Cancer International Consortium (Metabric) Study By Biochemically-Inspired Machine Learning, Peter Rogan, Eliseos J. Mucaki, Katherina Baranova, Huy Q. Pham, Iman Rezaeian, Dimo Angelov, Alioune Ngom, Luis Rueda
Biochemistry Publications
Genomic aberrations and gene expression-defined subtypes in the large METABRIC patient cohort have been used to stratify and predict survival. The present study used normalized gene expression signatures of paclitaxel drug response to predict outcome for different survival times in METABRIC patients receiving hormone (HT) and, in some cases, chemotherapy (CT) agents. This machine learning method, which distinguishes sensitivity vs. resistance in breast cancer cell lines and validates predictions in patients; was also used to derive gene signatures of other HT (tamoxifen) and CT agents (methotrexate, epirubicin, doxorubicin, and 5-fluorouracil) used in METABRIC. Paclitaxel gene signatures exhibited the best performance, …
Birc6 Mediates Imatinib Resistance Independently Of Mcl-1, Denis O. Okumu, Michael P. East, Merlin Levine, Laura E. Herring, Raymond Zhang, Thomas S.K. Gilbert, David Litchfield, Yanping Zhang, Lee M. Graves
Birc6 Mediates Imatinib Resistance Independently Of Mcl-1, Denis O. Okumu, Michael P. East, Merlin Levine, Laura E. Herring, Raymond Zhang, Thomas S.K. Gilbert, David Litchfield, Yanping Zhang, Lee M. Graves
Biochemistry Publications
© 2017 Okumu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Baculoviral IAP repeat containing 6 (BIRC6) is a member of the inhibitors of apoptosis proteins (IAPs), a family of functionally and structurally related proteins that inhibit apoptosis. BIRC6 has been implicated in drug resistance in several different human cancers, however mechanisms regulating BIRC6 have not been extensively explored. Our phosphoproteomic analysis of an imatinib-resistant chronic myelogenous leukemia (CML) cell line (MYL-R) …
Discovery And Validation Of Information Theory-Based Transcription Factor And Cofactor Binding Site Motifs., Ruipeng Lu, Eliseos J Mucaki, Peter K Rogan
Discovery And Validation Of Information Theory-Based Transcription Factor And Cofactor Binding Site Motifs., Ruipeng Lu, Eliseos J Mucaki, Peter K Rogan
Biochemistry Publications
Data from ChIP-seq experiments can derive the genome-wide binding specificities of transcription factors (TFs) and other regulatory proteins. We analyzed 765 ENCODE ChIP-seq peak datasets of 207 human TFs with a novel motif discovery pipeline based on recursive, thresholded entropy minimization. This approach, while obviating the need to compensate for skewed nucleotide composition, distinguishes true binding motifs from noise, quantifies the strengths of individual binding sites based on computed affinity and detects adjacent cofactor binding sites that coordinate with the targets of primary, immunoprecipitated TFs. We obtained contiguous and bipartite information theory-based position weight matrices (iPWMs) for 93 sequence-specific TFs, …