Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 254

The DOI matches its Crossref record.

RETRACTED: Thermostable cellulases: Current status and perspectives

Patel, Anil K., Singhania, Reeta Rani, Sim, Sang Jun, Pandey, Ashok·2019·Bioresource Technology

Abstract

It is envisaged that the utilization of lignocellulosic biomass for ethanol production for transport sector, would make cellulases the most demanded industrial enzyme. The greatest potential of cellulolytic enzymes lies in ethanol production from biomass by enzymatic hydrolysis of cellulose but low thermostability and low titer of cellulase production resulting into high cost of the enzyme which is the major set-back. A number of research groups are working on cellulase to improve its thermostability so as to be able to perform hydrolysis at elevated temperatures which would eventually increase the efficiency of cellulose hydrolysis. The technologies developed from lignocellulosic biomass via cellulose hydrolysis promise environmental and economical sustainability in the long run along with non-dependence on nonrenewable energy source. This review deals with the important sources of thermostable cellulases, mechanism, its regulation, strategies to enhance the thermostability further with respect to its importance for biofuel applications.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/j.biortech.2019.01.049This paper is marked retracted.

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 254

Metadata

Authors
Patel, A. K., Singhania, R. R., Sim, S. J., & Pandey, A.
Venue
Bioresource Technology
Publisher
Elsevier BV
Published
2019-05
Volume
279
Pages
385-392
ISSN
0960-8524 (ISSN-L)
OpenAlex
W2910355691
Cited by
254
References
0
FWCI
11.03
Type
journal article
Language
en
Status
Retracted
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: RETRACTED: Thermostable cellulases: Current status and perspectives. https://app.cochat.ai/papers/10.1016/j.biortech.2019.01.049
The paper
Patel, A. K., Singhania, R. R., Sim, S. J., & Pandey, A. (2019). RETRACTED: Thermostable cellulases: Current status and perspectives. Bioresource Technology. https://doi.org/10.1016/j.biortech.2019.01.049

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.