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  1. Book: Systems biology of biomarkers

    Rodland, Karin D.

    (Disease markers ; 28,4)

    2010  

    Author's details guest ed.: Karin D. Rodland
    Series title Disease markers ; 28,4
    Collection
    Language English
    Size S. 195 - 266 : Ill., graph. Darst.
    Publisher IOS Press
    Publishing place Amsterdam u.a.
    Publishing country Netherlands
    Document type Book
    HBZ-ID HT016437792
    ISBN 978-1-60750-584-6 ; 1-60750-584-3
    Database Catalogue ZB MED Medicine, Health

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    Zs A 1856 -28- not available for loan Zeitschriften-Lesesaal

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  2. Book: Mass spectrometry and biomarker development

    Rodland, Karin D.

    (Disease markers ; 20,3)

    2004  

    Author's details guest ed.: Karin D. Rodland
    Series title Disease markers ; 20,3
    Collection
    Language English
    Size S. 129 - 178 : Ill., graph. Darst.
    Publisher IOS Press
    Publishing place Amsterdam u.a.
    Publishing country Netherlands
    Document type Book
    HBZ-ID HT015976169
    ISBN 1-58603-461-8 ; 978-1-58603-461-0
    Database Catalogue ZB MED Medicine, Health

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  3. Article ; Online: Oncoproteomic profiling of AML: moving beyond genomics.

    Joshi, Sunil K / Tognon, Cristina E / Druker, Brian J / Rodland, Karin D

    Expert review of proteomics

    2023  Volume 19, Issue 7-12, Page(s) 283–287

    MeSH term(s) Humans ; Mutation ; Drug Resistance, Neoplasm ; Genomics ; Leukemia, Myeloid, Acute/genetics ; Protein Kinase Inhibitors/pharmacology
    Chemical Substances Protein Kinase Inhibitors
    Language English
    Publishing date 2023-02-10
    Publishing country England
    Document type Editorial ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2299100-1
    ISSN 1744-8387 ; 1478-9450
    ISSN (online) 1744-8387
    ISSN 1478-9450
    DOI 10.1080/14789450.2023.2176757
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Introduction to the special issue on Applications of Artificial Intelligence in Biomarker Research.

    Rodland, Karin D / Webb-Robertson, Bobbie-Jo / Srivastava, Sudhir

    Cancer biomarkers : section A of Disease markers

    2022  Volume 33, Issue 2, Page(s) 171–172

    MeSH term(s) Algorithms ; Artificial Intelligence ; Biomarkers ; Humans
    Chemical Substances Biomarkers
    Language English
    Publishing date 2022-03-06
    Publishing country Netherlands
    Document type Editorial
    ZDB-ID 2203517-5
    ISSN 1875-8592 ; 1574-0153 ; 1875-8592
    ISSN (online) 1875-8592 ; 1574-0153
    ISSN 1875-8592
    DOI 10.3233/CBM-229001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Circulating Cancer Biomarkers.

    Lokshin, Anna / Bast, Robert C / Rodland, Karin

    Cancers

    2021  Volume 13, Issue 4

    Abstract: Cancer is among the major public health problems worldwide, representing the leading cause of morbidity and mortality in industrialized countries [ ... ]. ...

    Abstract Cancer is among the major public health problems worldwide, representing the leading cause of morbidity and mortality in industrialized countries [...].
    Language English
    Publishing date 2021-02-15
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers13040802
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: As if biomarker discovery isn't hard enough: the consequences of poorly characterized reagents.

    Rodland, Karin D

    Clinical chemistry

    2013  Volume 60, Issue 2, Page(s) 290–291

    MeSH term(s) Biomarkers/analysis ; Early Diagnosis ; High-Throughput Screening Assays/methods ; Humans ; Neoplasm Staging ; Neoplasms/diagnosis ; Neoplasms/pathology ; Reagent Kits, Diagnostic/standards ; Sensitivity and Specificity
    Chemical Substances Biomarkers ; Reagent Kits, Diagnostic
    Language English
    Publishing date 2013-12-04
    Publishing country England
    Document type Editorial
    ZDB-ID 80102-1
    ISSN 1530-8561 ; 0009-9147
    ISSN (online) 1530-8561
    ISSN 0009-9147
    DOI 10.1373/clinchem.2013.216382
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Use of Longitudinal Serum Analysis and Machine Learning to Develop a Classifier for Cancer Early Detection.

    Madda, Rashmi / Petyuk, Vladislav A / Wang, Yi-Ting / Shi, Tujin / Shriver, Craig D / Rodland, Karin D / Liu, Tao

    Methods in molecular biology (Clifton, N.J.)

    2023  Volume 2628, Page(s) 579–592

    Abstract: Early detection of solid tumors through a simple screening process, such as the proteomic analysis of biofluids, has the potential to significantly alter the management and outcomes of cancers. The application of advanced targeted proteomics measurements ...

    Abstract Early detection of solid tumors through a simple screening process, such as the proteomic analysis of biofluids, has the potential to significantly alter the management and outcomes of cancers. The application of advanced targeted proteomics measurements and data analysis strategies to uniformly collected serum or plasma samples would enable longitudinal studies of cancer risk, progression, and response to therapy that have the potential to significantly reduce cancer burden in general. In this article, we describe a generalizable workflow combining robust, multiplexed targeted proteomics measurements applied to longitudinal samples from the Department of Defense Serum Repository with a Random Forest machine learning method for developing and initially evaluating the performance of candidate biomarker panels for early detection of cancers. The effectiveness of this approach was demonstrated in a cohort of 175 head and neck squamous cell carcinoma patients. The outlined protocols include methods for sample preparation, instrument analysis, and data analysis and interpretation using this workflow.
    MeSH term(s) Humans ; Early Detection of Cancer ; Proteomics/methods ; Biomarkers ; Neoplasms/diagnosis ; Machine Learning
    Chemical Substances Biomarkers
    Language English
    Publishing date 2023-02-13
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-0716-2978-9_33
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Systems biology and biomarker discovery.

    Rodland, Karin D

    Disease markers

    2010  Volume 28, Issue 4, Page(s) 195–197

    MeSH term(s) Animals ; Biomarkers ; Humans ; Systems Biology
    Chemical Substances Biomarkers
    Keywords covid19
    Language English
    Publishing date 2010-06-09
    Publishing country United States
    Document type Editorial
    ZDB-ID 604951-5
    ISSN 1875-8630 ; 0278-0240
    ISSN (online) 1875-8630
    ISSN 0278-0240
    DOI 10.3233/DMA-2010-0706
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    ab Jg. 2022: Lesesaal (EG)
    Einzelsignatur: Show issues

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  9. Article ; Online: Moonshot Objectives: Catalyze New Scientific Breakthroughs-Proteogenomics.

    Rodland, Karin D / Piehowski, Paul / Smith, Richard D

    Cancer journal (Sudbury, Mass.)

    2018  Volume 24, Issue 3, Page(s) 121–125

    Abstract: Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their ... ...

    Abstract Breaking down the silos between disciplines to accelerate the pace of cancer research is a key paradigm for the Cancer Moonshot. Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids-DNA, RNA, and their modifications-and a focus on proteins and protein function. Proteogenomics represents a fusion of those two approaches, leveraging the strengths of each to provide a more integrated vision of the flow of information from DNA to RNA to protein and eventually function at the molecular level. Proteogenomic studies have been incorporated into multiple activities associated with the Cancer Moonshot, demonstrating substantial added value. Innovative study designs integrating genomic, transcriptomic, and proteomic data, particularly those using clinically relevant samples and involving clinical trials, are poised to provide new insights regarding cancer risk, progression, and response to therapy.
    MeSH term(s) DNA/genetics ; Genomics/methods ; Humans ; Neoplasms/genetics ; Neoplasms/metabolism ; Proteins/genetics ; Proteogenomics/methods ; Proteomics/methods ; RNA/genetics ; Transcriptome/genetics
    Chemical Substances Proteins ; RNA (63231-63-0) ; DNA (9007-49-2)
    Language English
    Publishing date 2018-05-22
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 2018400-1
    ISSN 1540-336X ; 1528-9117 ; 1081-4442
    ISSN (online) 1540-336X
    ISSN 1528-9117 ; 1081-4442
    DOI 10.1097/PPO.0000000000000315
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.MO 163: Show issues

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  10. Article: Characterization of the Ovarian Tumor Peptidome.

    Liu, Tao / Rodland, Karin D / Smith, Richard D

    Vitamins and hormones

    2018  Volume 107, Page(s) 515–531

    Abstract: Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of the tumor peptidome has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to ...

    Abstract Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of the tumor peptidome has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the tumors peptidome information in cancer research have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. To address this need, we have recently developed an effective and robust analytical platform as well as a novel informatics approach for comprehensive analyses of tissue peptidomes. The ability of this new peptidomics pipeline for high-throughput, comprehensive, and quantitative peptidomics analysis, as well as the suitability of clinical ovarian tumor samples with postexcision delay limited to less than 60min before freezing for peptidomics analysis, has been demonstrated. These initial analyses set a stage for further determination of molecular details and functional significance of the peptidomic activities in ovarian cancer.
    MeSH term(s) Carcinoma/metabolism ; Carcinoma/pathology ; Carcinoma/surgery ; Chromatography, High Pressure Liquid ; Chymotrypsin/chemistry ; Chymotrypsin/metabolism ; Cluster Analysis ; Databases, Protein ; Double Effect Principle ; Female ; Humans ; Molecular Weight ; Neoplasm Grading ; Neoplasm Proteins/chemistry ; Neoplasm Proteins/metabolism ; Neoplasm Staging ; Ovarian Neoplasms/metabolism ; Ovarian Neoplasms/pathology ; Ovarian Neoplasms/surgery ; Ovary/metabolism ; Ovary/pathology ; Ovary/surgery ; Peptide Fragments/chemistry ; Peptide Fragments/metabolism ; Protein Stability ; Proteolysis ; Proteomics/methods ; Regression Analysis ; Tandem Mass Spectrometry
    Chemical Substances Neoplasm Proteins ; Peptide Fragments ; Chymotrypsin (EC 3.4.21.1)
    Language English
    Publishing date 2018-02-22
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 201161-x
    ISSN 2162-2620 ; 0083-6729
    ISSN (online) 2162-2620
    ISSN 0083-6729
    DOI 10.1016/bs.vh.2018.01.020
    Database MEDical Literature Analysis and Retrieval System OnLINE

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