An Introduction to Sequence Similarity (“Homology”) Searching

By Gary D. Stormo. Current Protocols in Bioinformatics, 2009

563 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Molecular Biology, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b06a1516938ffb3a8208ccf9ceb6ed56518c5759

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Sebastian Gehrmann
2. Hendrik Strobelt
3. Inkit Padhi
4. Aleksandra Mojsilovic
5. Pin-Yu Chen
6. Payel Das
7. Vijil Chenthamarakshan
8. Kahini Wadhawan

In Molecular Biology

1. Pin-Yu Chen
2. Payel Das
3. Vijil Chenthamarakshan
4. Tom Sercu
5. Hendrik Strobelt
6. Sebastian Gehrmann
7. Inkit Padhi

In Signal Processing

1. Sebastian Gehrmann
2. Hendrik Strobelt
3. Pin-Yu Chen
4. Vijil Chenthamarakshan
5. Tom Sercu

Citations in the corpus

• Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations (2021, methodology): “Typically, when querying the UniProt non-redundant database, which contains around 220 million sequences, E values of ≤ 0.001 are used to infer homology 56 .”