Evidence map›Paper›PMID 26074668›Full record

ReviewIndustrial & engineering chemistry research2015

High Throughput Screening and Selection Methods for Directed Enzyme Evolution.

Han Xiao, Zehua Bao, Huimin Zhao

Abstract readReview
In one paragraph

Review in Industrial & engineering chemistry research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.

0numbers the graph read from it
0cells of the map it votes in
70citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

70 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Genuine Directed Evolution In Test Tube (GENie).bioRxiv : the preprint server for biology · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Advances in Machine Learning Models for Predicting Enzyme Kinetic Parameters.Journal of chemical information and modeling · 2026
    Review
  10. Review
  11. Horticulture research · 2025
    Article
  12. Article
  13. Review
  14. High-ThroughputACS central science · 2025
    Article
  15. Article
  16. Article
  17. Article
  18. Advances in the Directed Evolution of Computer-aided Enzymes.Current topics in medicinal chemistry · 2025
    Review
  19. Article
  20. Review

10 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Han XiaoDepartment of Chemical and Biomolecular Engineering, Department of Biochemistry, and Departments of Chemistry and Bioengineering and Institute for Genomic Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Zehua BaoDepartment of Chemical and Biomolecular Engineering, Department of Biochemistry, and Departments of Chemistry and Bioengineering and Institute for Genomic Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.
Huimin ZhaoDepartment of Chemical and Biomolecular Engineering, Department of Biochemistry, and Departments of Chemistry and Bioengineering and Institute for Genomic Biology, University of Illinois at Urbana-Champaign , Urbana, Illinois 61801, United States.

Funding

Structural Elucidation and Biosynthesis P01GM077596 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI METCALF, WILLIAM W · 2007 to 2016
$15.3M
NIGMS NIH HHS P01 GM077596
6 · The paper itself

Abstract

Successful evolutionary enzyme engineering requires a high throughput screening or selection method, which considerably increases the chance of obtaining desired properties and reduces the time and cost. In this review, a series of high throughput screening and selection methods are illustrated with significant and recent examples. These high throughput strategies are also discussed with an emphasis on compatibility with phenotypic analysis during directed enzyme evolution. Lastly, certain limitations of current methods, as well as future developments, are briefly summarized.

Identifiers

PMID26074668
PMCPMC4461044

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.