Name
Abstract | ||
|---|---|---|
We introduce a new method for filtering noisy 3C interactions that selects subsets of interactions that obey metric constraints of various strictness. We demonstrate that, although the problem is computationally hard, near-optimal results are often attainable in practice using well-designed heuristics and approximation algorithms. Further, we show that, compared with a standard technique, this metric filtering approach leads to (a) subgraphs with higher total statistical significance, (b) lower embedding error, (c) lower sensitivity to initial conditions of the embedding algorithm, and (d) structures with better agreement with light microscopy measurements. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33122-0_23 | WABI |
Keywords | Field | DocType |
chromosome conformation data,embedding error,better agreement,resolving spatial inconsistency,lower sensitivity,approximation algorithm,initial condition,higher total statistical significance,embedding algorithm,near-optimal result,light microscopy measurement,obey metric constraint | Approximation algorithm,Combinatorics,Embedding,Computer science,Algorithm,Filter (signal processing),Heuristics | Conference |
Citations | PageRank | References |
2 | 0.47 | 5 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Geet Duggal | 1 | 31 | 4.50 |
| Rob Patro | 2 | 111 | 12.98 |
| Emre Sefer | 3 | 34 | 5.12 |
| Hao Wang | 4 | 60 | 8.12 |
| Darya Filippova | 5 | 38 | 5.83 |
| Samir Khuller | 6 | 4053 | 368.49 |
| Carl Kingsford | 7 | 695 | 54.27 |