Table 1.
Summary statistics of the predictions for the 30 tissues examined.
| Tissue | No. of CRMs | No. of target genes | Important TFs |
| Bladder | 58 | 35 | SREBP-1, NRF-1, NF-Y, ETF, MAX |
| Blood | 319 | 150 | FOXJ2, ELF-1, ETF, CDP, PEA3 |
| bone | 4 | 4 | OCT-1, RFX1, EF-C, FOXJ2, NKX3A |
| bone marrow | 138 | 73 | SREBP-1, NRF-1, STAT1, HLF, TEF |
| brain | 757 | 149 | FREAC-7, OCT-1, SOX-9, FREAC-3, NKX6-2 |
| cervix | 174 | 90 | ETF, NRF-1, SP1, AP-2, C-MYC/MAX |
| colon | 225 | 68 | CDP, AFP1, HNF-1, OCT-1, ALX-4 |
| eye | 242 | 78 | FOXJ2, POU3F2, OCT-1, CHX10, CRX |
| heart | 192 | 62 | MEF-2, POU3F2, GATA-6, AP-1, IRF1 |
| kidney | 180 | 83 | HNF-1, COUP-TF/HNF-4, CRX, OCT-1 |
| larynx | 225 | 99 | ETF, SP1, NRF-1, AP-2, WHN |
| liver | 300 | 110 | HNF-1, ALX-4, HNF-3alpha, C/EBPgamma |
| lung | 64 | 28 | ETF, MTF-1, C-MYC/MAX, LHX3, NRF-1 |
| lymph node | 194 | 111 | ICSBP, PU.1, ETF, ELK-1, NRF-1 |
| mammary gland | 180 | 69 | RSRFC4, CDP, MEF-2, FAC1, LHX3 |
| muscle | 169 | 69 | MEF-2, RSRFC4, SRF, MYOD, CDP_CR3 |
| ovary | 121 | 47 | VDR, MAZ, MZF1, SP1, CREB |
| pancreas | 110 | 48 | MYOD, ATF, SP1, E47, AREB6 |
| PNS | 260 | 55 | POU3F2, OCT-1, NKX6-2, HNF-6, HFH-3 |
| placenta | 121 | 57 | LHX3, AFP1, CHX10, NKX6-2, CDP |
| prostate | 212 | 64 | LHX3, POU3F2, CDC5, C/EBPgamma, CART-1 |
| skin | 50 | 28 | AREB6, LMO2_COMPLEX, ALX-4, ARP-1 |
| small intestine | 435 | 68 | POU3F2, LHX3, NKX6-2, HNF-1, FOXD3 |
| soft tissue | 217 | 70 | FOXO4, C/EBPgamma, FOXO1, SRY, RSRFC4 |
| spleen | 94 | 44 | RSRFC4, LBP-1, CDP, MEF-2, NF-KAPPAB |
| stomach | 131 | 76 | ETF, SP1, AP-2gamma, AREB6, SRY |
| testis | 579 | 296 | NRF-1, ETF, SP1, AP-2, C-MYC/MAX |
| thymus | 155 | 47 | POU3F2, NKX6-2, E4BP4, TAX/CREB, ETF |
| tongue | 183 | 104 | ETF, SP1, NRF-1, HIF-1, CREB |
| uterus | 143 | 28 | POU3F2, OCT-1, E4BP4, POU1F1, NKX6-1 |
| Total | 6232 | 2310 | |
Important TFs of a tissue are the top 5 TFs which contribute most to the potential energies of the CRMs.