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Current Opinion in Systems Biology
H-index 16

Current Opinion in Systems Biology

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Biology and Biochemistry 547 26 29 11

Additional Metrics

Number of Best Scientists*: 59
Documents by Best Scientists*: 57
Top 100 Ranked Scientists*: 5
SCIMAGO H-index: 38
SCIMAGO SJR: 1.702
Impact Factor: 2.2

Overview

Top Research Topics at Current Opinion in Systems Biology?

The topics of Computational biology, Systems biology, Data science, Synthetic biology and Bioinformatics are the focal point of discussions in the journal. Topics in Computational biology were tackled in line with various other fields like Cancer, Genetics, Genome, Genomics and Gene. The study on Systems biology presented in the journal intersects with subjects under the field of Management science.

The journal facilitates the exploration of Data science in relation to the field of Field (computer science).

  • Computational biology (33.42%)
  • Systems biology (17.88%)
  • Data science (10.36%)

What are the most cited papers published in the journal?

  • Single cells make big data: New challenges and opportunities in transcriptomics (111 citations)
  • Machine learning and image-based profiling in drug discovery. (76 citations)
  • Current state and applications of microbial genome-scale metabolic models (67 citations)

Research areas of the most cited articles at Current Opinion in Systems Biology:

The journal papers are organized to address concerns in the fields of Computational biology, Systems biology, Cell biology, Neuroscience and Data science. Synthetic biology is a focus of the presented Computational biology works in the journal publications and they dives deep in Synthetic biology. The most cited articles explore topics in Systems biology which can be helpful for research in disciplines like Organism, Cognitive science and Agent-based model.

What topics the last edition of the journal is best known for?

  • Gene
  • DNA
  • Genetics

The previous edition focused in particular on these issues:

The journal explores disciplines such as Computational biology, Synthetic biology, Data science, Systems biology and Biochemical engineering. The research on Computational biology tackled can also make contributions to studies in the areas of Cell, Cell signaling, Gene expression, Gene and Rational design. The journal addresses concerns in Synthetic biology which are intertwined with other disciplines, such as Control theory, Software engineering, DNA and Robustness (evolution).

Issues in Data science were discussed, taking into consideration concepts from other disciplines like Data integration and Leverage (statistics). While work presented in it provided substantial information on Systems biology, it also covered topics in Multiscale modeling and Intracellular. The overlapping concepts between Model selection and Inference are the key highlights of Biochemical engineering study.

The most cited articles from the last journal are:

  • On structural and practical identifiability (12 citations)
  • Statistical and computational challenges for whole cell modelling (6 citations)
  • The landscape of cell-cell communication through single-cell transcriptomics. (5 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Current Opinion in Systems Biology (based on the number of publications) are:

  • Michael P. H. Stumpf (5 papers) published 4 papers at the last edition,
  • Jens Nielsen (5 papers) published 1 paper at the last edition,
  • Edda Klipp (4 papers) published 1 paper at the last edition,
  • Shinya Kuroda (4 papers) published 1 paper at the last edition,
  • Jonathan R. Karr (4 papers) published 2 papers at the last edition, 1 more than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Current Opinion in Systems Biology (based on the number of publications) are:

  • Harvard University (13 papers) published 4 papers at the last edition the same number as at the previous edition,
  • Imperial College London (11 papers) published 6 papers at the last edition,
  • ETH Zurich (11 papers) published 3 papers at the last edition,
  • University of Cambridge (9 papers) absent at the last edition,
  • École Polytechnique Fédérale de Lausanne (7 papers) published 2 papers at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 10.26% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 28.57% were posted by at least one author from the top 10 institutions publishing in the journal. Another 4.29% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 21.43% of all publications and 45.71% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Prospects in Systems Biology

There is a myriad of opportunities available for individuals with a degree in systems biology. A career path in this discipline can lead to various roles including, but not limited to, academia, the pharmaceutical industry, the biotechnology sector, and even opportunities in nutrition. For instance, a degree in systems biology can help springboard a career in the field of nutrition, specifically as a nutritionist. Nutritionists evaluate the health of their patients and determine appropriate dietary plans to either maintain or improve their patients' health. With a strong background in systems biology, nutritionists gain a broad understanding of the human biological systems and how nutrients are processed, which comes in handy when designed personalized dietary plans. If you're interested in becoming a nutritionist in Maine, it's crucial to understand the process, including the coursework required, licensure prerequisites, and the general timeline involved. This journey might differ depending on your current academic standing and your career goals. It is of utmost importance that prospective nutritionists align their interest in nutritional sciences with a course or program that gives them the best grounding in preparing for a fulfilling career. Learn more about how long does it take to become a nutritionist in Maine and the specific steps you can take to join this profession. Whether you're fresh from high school, a recent college graduate, or a professional contemplating a career shift, your interest in systems biology might be the catalyst to jumpstart your career in the nutrition field. Remember, the world is your oyster, and systems biology might be the lens through which you view it!

Top Publications

  • Advances in constraint-based modelling of microbial communities

    Almut Heinken;Arianna Basile;Arianna Basile;Ines Thiele

    (2021)
    57 Citations
  • Real-time, personalized medicine through wearable sensors and dynamic predictive modeling: a new paradigm for clinical medicine.

    Jonathan Tyler;Sung Won Choi;Muneesh Tewari

    (2020)
    57 Citations
  • Mathematical modeling of proteome constraints within metabolism

    Yu Chen;Jens B Nielsen;Jens B Nielsen

    (2021)
    40 Citations
  • Machine learning applications in genome-scale metabolic modeling

    Yeji Kim;Gi Bae Kim;Sang Yup Lee

    (2021)
    36 Citations
  • Recent advances in trajectory inference from single-cell omics data

    Louise Deconinck;Robrecht Cannoodt;Wouter Saelens;Wouter Saelens;Bart Deplancke;Bart Deplancke

    (2021)
    35 Citations
  • Graph Representation Learning for Single Cell Biology

    Leon Hetzel;David S. Fischer;Stephan Günnemann;Fabian J. Theis

    (2021)
    32 Citations
  • Recent advances in non-model bacterial chassis construction

    (2023)
    19 Citations
  • Glycolysis: How a 300yr long research journey that started with the desire to improve alcoholic beverages kept revolutionizing biochemistry

    Nana-Maria Grüning;Markus Ralser;Markus Ralser

    (2021)
    14 Citations
  • Metabolic dynamics during the cell cycle

    (2022)
    13 Citations
  • The evolution of the metabolic network over long timelines

    Markus Ralser;Markus Ralser;Sreejith J. Varma;Richard A. Notebaart

    (2021)
    12 Citations

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Best Scientists Contributing to This Journal