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Cancer Systems Biology

Overview of attention for book
Cover of 'Cancer Systems Biology'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Detection of Combinatorial Mutational Patterns in Human Cancer Genomes by Exclusivity Analysis
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    Chapter 2 Discovering Altered Regulation and Signaling Through Network-based Integration of Transcriptomic, Epigenomic, and Proteomic Tumor Data
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    Chapter 3 Analyzing DNA Methylation Patterns During Tumor Evolution
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    Chapter 4 MicroRNA Networks in Breast Cancer Cells
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    Chapter 5 Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels
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    Chapter 6 Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells
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    Chapter 7 Perseus: A Bioinformatics Platform for Integrative Analysis of Proteomics Data in Cancer Research
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    Chapter 8 Quantitative Analysis of Tyrosine Kinase Signaling Across Differentially Embedded Human Glioblastoma Tumors
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    Chapter 9 Prediction of Clinical Endpoints in Breast Cancer Using NMR Metabolic Profiles
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    Chapter 10 Stochastic and Deterministic Models for the Metastatic Emission Process: Formalisms and Crosslinks
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    Chapter 11 Mechanically Coupled Reaction-Diffusion Model to Predict Glioma Growth: Methodological Details
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    Chapter 12 Profiling Tumor Infiltrating Immune Cells with CIBERSORT
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    Chapter 13 Systems Biology Approaches in Cancer Pathology
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    Chapter 14 Bioinformatics Approaches to Predict Drug Responses from Genomic Sequencing
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    Chapter 15 A Robust Optimization Approach to Cancer Treatment under Toxicity Uncertainty
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    Chapter 16 Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response
  18. Altmetric Badge
    Chapter 17 Methods for High-throughput Drug Combination Screening and Synergy Scoring
Attention for Chapter 17: Methods for High-throughput Drug Combination Screening and Synergy Scoring
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  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

3 tweeters


5 Dimensions

Readers on

90 Mendeley
1 CiteULike
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Chapter title
Methods for High-throughput Drug Combination Screening and Synergy Scoring
Chapter number 17
Book title
Cancer Systems Biology
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7493-1_17
Pubmed ID
Book ISBNs
978-1-4939-7492-4, 978-1-4939-7493-1

Liye He, Evgeny Kulesskiy, Jani Saarela, Laura Turunen, Krister Wennerberg, Tero Aittokallio, Jing Tang


Gene products or pathways that are aberrantly activated in cancer but not in normal tissue hold great promises for being effective and safe anticancer therapeutic targets. Many targeted drugs have entered clinical trials but so far showed limited efficacy mostly due to variability in treatment responses and often rapidly emerging resistance. Toward more effective treatment options, we will need multi-targeted drugs or drug combinations, which selectively inhibit the viability and growth of cancer cells and block distinct escape mechanisms for the cells to become resistant. Functional profiling of drug combinations requires careful experimental design and robust data analysis approaches. At the Institute for Molecular Medicine Finland (FIMM), we have developed an experimental-computational pipeline for high-throughput screening of drug combination effects in cancer cells. The integration of automated screening techniques with advanced synergy scoring tools allows for efficient and reliable detection of synergistic drug interactions within a specific window of concentrations, hence accelerating the identification of potential drug combinations for further confirmatory studies.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 1%
Unknown 89 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 27%
Researcher 16 18%
Student > Master 8 9%
Student > Bachelor 8 9%
Student > Postgraduate 5 6%
Other 19 21%
Unknown 10 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 33%
Agricultural and Biological Sciences 16 18%
Pharmacology, Toxicology and Pharmaceutical Science 5 6%
Medicine and Dentistry 5 6%
Chemistry 3 3%
Other 9 10%
Unknown 22 24%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2019.
All research outputs
of 14,249,108 outputs
Outputs from Methods in molecular biology
of 8,750 outputs
Outputs of similar age
of 358,267 outputs
Outputs of similar age from Methods in molecular biology
of 1,804 outputs
Altmetric has tracked 14,249,108 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,750 research outputs from this source. They receive a mean Attention Score of 2.3. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 358,267 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,804 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.