Table 1.
Motif discovery algorithms
| No. | Algorithm | Operating principle | Ref. |
|---|---|---|---|
| Enumerative approach | |||
| 1 | YMF | (29) | |
| 2 | DREME | Simple word- based | (9) |
| 3 | oligonucleotide analysis | (30) | |
| 4 | CisFinder | (10) | |
| 5 | By Thomas et al | Simple word-based with Clustering technique | (31) |
| 6 | POSMO | (32) | |
| 7 | Weeder | (7) | |
| 8 | FMotif | (11) | |
| 9 | By G. Pavesi | (33) | |
| 10 | MITRA | Tree-based | (34) |
| 11 | CENSUS | (35) | |
| 12 | RISOTTO | (36) | |
| 13 | SLI-REST | (37) | |
| 14 | DRIMust | (38) | |
| 15 | MCES | Tree based with clustering technique | (12) |
| 16 | WINNOWER | (39) | |
| 17 | Pruner | (40) | |
| 18 | cWINNOWER | (41) | |
| 19 | By Sze et al | (42) | |
| 20 | RecMotif | Graph-theoretic | (43) |
| 21 | ListMotif | (44) | |
| 22 | TreeMotif | (45) | |
| 23 | GWM | (46) | |
| 24 | GWM2 | (47) | |
| 25 | Voting | (48) | |
| 26 | PMS1 | (49) | |
| 27 | PMS2 | (49) | |
| 28 | PMS3 | (49) | |
| 29 | By Sze et al | (50) | |
| 30 | PMSi | (51) | |
| 31 | PMSP | Fixed candidates | (51) |
| 32 | Stemming | (52) | |
| 33 | PMS4 | (53) | |
| 34 | PMS5 | (54) | |
| 35 | PMS6 | (55) | |
| 36 | PairMotif | (56) | |
| 37 | iTriplet | (57) | |
| 38 | PMSPrune | (58) | |
| 39 | Pampa | (59) | |
| 40 | PMS3p | (60) | |
| 41 | Provable | Modified candidate | (61) |
| 42 | qPMSPruneI | (62) | |
| 43 | qPMS7 | (62) | |
| 44 | By Tanaka et al | (63) | |
| 45 | Random projection | (64) | |
| 46 | Uniform projection | Hashing | (65) |
| 47 | Low-dispersion projection | (66) | |
| 48 | MULTIPROFILER | Extended sample-driven (ESD) | (67) |
| 49 | Pattern Branching | (68) | |
| 50 | Ref Select | Reference selection | (69) |
| Probabilistic approach | |||
| 51 | MEME | (14) | |
| 52 | STEME | EM | (15) |
| 53 | EXTREME | (16) | |
| 54 | Profile Branching | (68) | |
| 55 | APMotif | EM with clustering | (70) |
| 56 | AlignACE | (17) | |
| 57 | SPWDM | (71) | |
| 58 | By Lawrence et al | Gibbs sampling | (72) |
| 59 | Motif- Sampler | (73) | |
| 60 | BioProspector | Gibbs Sampling with hidden markov | (18) |
| 62 | MITSU | (74) | |
| 63 | MCEMDA | Stochastic Expectation Maximization (sEM) | (75) |
| 64 | SEAM | (76) | |
| 65 | By Jensen et al | (13) | |
| 66 | LOGOS | (77) | |
| 67 | BaMM | (78) | |
| 68 | By Jääskinen et al | (79) | |
| 69 | By Frith et al | Baysian approach | (80) |
| 70 | SBaSeTraM | (81) | |
| 71 | By Wakefield et al | (82) | |
| 72 | MotifCut | (83) | |
| 73 | MCL-WMR | Graphic based | (84) |
| 74 | EPP | Entropy-based position projection | (6) |
| 75 | CONSENSUS | Greedy Algorithm | (85) |
| 76 | By Huang et al | heuristic algorithm | (86) |
| GA | |||
| 77 | St-GA | (87) | |
| 78 | GAMI | (88) | |
| 79 | FMGA | Simple GA | (89) |
| 80 | MDGA | (90) | |
| 81 | By Paul et al | (91) | |
| 82 | By Vijayvargiya et al | Clustering | (92) |
| 83 | By Gutierrez et al | (93) | |
| 84 | GARPS | (94) | |
| 85 | GAEM | (95) | |
| 86 | GADEM | (96) | |
| 87 | CompareProspector | (97) | |
| 88 | By Fatemeh et al | Hybrid | (98) |
| 89 | GEMFA | (99) | |
| 90 | MRPGA | (100) | |
| 91 | By Xiaochun et al | (101) | |
| 92 | GAME | (19) | |
| 93 | By Yetian et al | (102) | |
| 94 | By Li et al | Others | (103) |
| 95 | MOGAMOD | (104) | |
| PSO | |||
| 96 | PMbPSO | Standard PSO | (4) |
| 97 | LPBS | (105) | |
| 98 | PSOMF | (106) | |
| 99 | Lei et al | (107) | |
| 100 | Lei et al | (108) | |
| 101 | DSAPSO | Modified PSO | (109) |
| 102 | By Karabulut et al | (110) | |
| 103 | Lei et al | (111) | |
| 104 | Hardin et al | (112) | |
| 105 | GSA-PSO | Hybrid | (113) |
| 106 | SPSO-Lk | (114) | |
| ABC algorithm | |||
| 107 | Multiobjective ABC | (115) | |
| 108 | MO-ABC/DE | ABC | (116) |
| 109 | Consensus ABC | (8) | |
| ACO algorithm | |||
| 110 | Machhi et al | ACO with Gibbs sampling | (117) |
| 111 | MFACO | (118) | |
| 112 | Cheng et al | ACO with EM | (119) |
| CS algorithm | |||
| 113 | MACS | CS | (120) |
| Combinatorial | |||
| 114 | STGEMS | Enumerative and probalistic approaches | (121) |
| 115 | MDScan | (122) | |
| 116 | MUSA | Probabilstic and machine learning approaches | (123) |
| 117 | EMD | Multiple algorithms | (124) |
| 118 | MobyDick | Dictionary | (125) |
| 119 | WordSpy | (126) |