Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 354

The DOI matches its Crossref record.

miR-192 Mediates TGF-β/Smad3-Driven Renal Fibrosis

Open access
Chung, Arthur C.K., Huang, Xiao R., Meng, Xiaoming, Lan, Hui Y.·2010·Journal of the American Society of Nephrology

Abstract

Seed-chain-extend with k-mer seeds is a powerful heuristic technique for sequence alignment employed by modern sequence aligners. While effective in practice for both runtime and accuracy, theoretical guarantees on the resulting alignment do not exist for seed-chain-extend. In this work, we give the first rigorous bounds for the efficacy of seed-chain-extend with k-mers in expectation. Assume we are given a random nucleotide sequence of length ≈ n that is indexed (or seeded) and a mutated substring of length ≈ m ≤ n with mutation rate θ < 0.206. We prove that we can find a k = Θ(log n) for the k-mer size such that the expected runtime of seed-chain-extend under optimal linear gap cost chaining and quadratic time gap extension is O(mnf(θ) log n) where f(θ) < 2.43·θ holds as a loose bound. In fact, for reasonable θ = 0.05, f(θ) < 0.08, indicating nearly quasilinear running time in practice. The alignment also turns out to be good; we prove that more than 1 − O(1/√m) fraction of the homologous bases are recoverable under an optimal chain. We also show that our bounds work when k-mers are sketched, i.e. only a subset of all k-mers is selected. Under the open syncmer sketching method, one can sketch with decreasing density as a function of n and achieve asymptotically smaller chaining time, yet the same bounds for extension time and recoverability hold. In other words, sketching reduces chaining time without increasing alignment time or decreasing accuracy too much, justifying the effectiveness of sketching as a practical speedup in sequence alignment. We verify our results in simulation and conjecture that f(θ) can be further reduced.

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 · 10.1681/asn.2010020134

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 354

Metadata

Authors
Chung, A. C. K., Huang, X. R., Meng, X., & Lan, H. Y.
Venue
Journal of the American Society of Nephrology
Published
2010-08
Volume
21
Issue
8
Pages
1317-1325
ISSN
1046-6673 (ISSN-L)
OpenAlex
W2107724630
Cited by
354
References
0
FWCI
12.88
Type
journal article
Language
en
Open access
green

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: miR-192 Mediates TGF-β/Smad3-Driven Renal Fibrosis. https://app.cochat.ai/papers/10.1681/asn.2010020134
The paper
Chung, A. C. K., Huang, X. R., Meng, X., & Lan, H. Y. (2010). miR-192 Mediates TGF-β/Smad3-Driven Renal Fibrosis. Journal of the American Society of Nephrology. https://doi.org/10.1681/asn.2010020134

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.