Datasets:

reogine
/

Massive-Genomic-Interactions

gene string	noncodingRNA string	noncodingRNA_name string	noncodingRNA_fam string	feature string	label int64	chr string	start float64	end int64	strand string	gene_cluster_ID int64	source_dataset string	source_split string
AGGAGATGCCAGGGCTGAGTGTGAGTGAGGTGGGAACACAAACCAGCATC	AATGGATTTTTGGAGCAGG	hsa-miR-1246	mir-1246	exon	1	20	38,951,952	38,952,001	+	714	AGO2_CLASH_Hejret2023	train
TAGAACAGTCCAGAAGCCTGAGAGACAGTGGCCCCTTGATAATCTGGGTC	TCCCTGAGACCCTAACTTGTGA	hsa-miR-125b-5p	mir-10	three_prime_utr	1	22	37,666,528	37,666,577	+	3,078	AGO2_CLASH_Hejret2023	train
CAGCGGTGCCTCAACCGAGCGTCCAAGCTCTTTCCATTTTTGCTCCTGCA	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	null	1	19	33,177,120	33,177,169	+	3	AGO2_CLASH_Hejret2023	train
CCTGCTGGCCCCACAGGACCTCATCCCTGATGTGCTGCAGAGCAATGACG	TAGCAGCACATCATGGTTTACA	hsa-miR-15b-5p	mir-15	exon	1	8	144,435,019	144,435,068	-	378	AGO2_CLASH_Hejret2023	train
TTTGTAAACTAACCCCTGGGAAATTTGAAATTACCTGATAACTTAAGACT	TTATCAGAATCTCCAGGGGTAC	hsa-miR-361-5p	mir-361	three_prime_utr	1	X	120,257,166	120,257,215	+	3,142	AGO2_CLASH_Hejret2023	train
AGCACATGGAGCACGGGATTAGATGCACAAACCTATTTAGGGAACTATTT	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	three_prime_utr	1	10	63,623,455	63,623,504	+	3,464	AGO2_CLASH_Hejret2023	train
GTGATTATAAAATCATGAAGCAGGTAAAGGGAGGGGCAAGCCCCCAAACT	TCCCTGAGACCCTTTAACCTGTGA	hsa-miR-125a-5p	mir-10	three_prime_utr	1	12	122,272,266	122,272,315	-	1,404	AGO2_CLASH_Hejret2023	train
AAACAACTGACTTCATACCCCTGCCTCACGAAAACCCAAAAGACACAGCT	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr	1	5	14,710,921	14,710,970	-	837	AGO2_CLASH_Hejret2023	train
CAACTCTTCAAGGAAAATTCGTATTTGCAGTGGGAAGAATAAGTAACATT	TGAGGTAGTAGGTTGTGTGGTT	hsa-let-7b-5p	let-7	five_prime_utr	1	15	89,113,774	89,113,823	+	2,383	AGO2_CLASH_Hejret2023	train
TACGGTATTTAATGGGGCCCAGAATGGTGTGTCTCAGCTAATCCAAAGGG	TAGCAGCACGTAAATATTGGCG	hsa-miR-16-5p	mir-15	exon	1	2	175,179,196	175,179,245	-	1,509	AGO2_CLASH_Hejret2023	train
CACTCACCATCAACTCTGTTAGCCCAATTGCCCTGCTGAACAACTGCCTG	TGCGGGGCTAGGGCTAACAGCA	hsa-miR-744-5p	mir-744	three_prime_utr	1	22	44,495,118	44,495,167	-	3,291	AGO2_CLASH_Hejret2023	train
GATGCAGCAAACTTCAGTGTTGTCATGTTTTAAGAAATTGCCACAGCCAC	ACGTTGGCTCTGGTGGTG	hsa-miR-1306-3p	mir-1306	null	1	6	28,424,396	28,424,445	-	693	AGO2_CLASH_Hejret2023	train
ACCCTGTCCTCCCACCCCTCCCCACTCATCACTAAACAGAGTAAAATGTG	TGAGGTAGTAGGTTGTATAGTT	hsa-let-7a-5p	let-7	three_prime_utr	1	21	46,004,037	46,004,086	+	213	AGO2_CLASH_Hejret2023	train
TTACCTACGTGAAGGAAAATGCCCGCTCGCCCAGCTCCGTCACCGGTAAC	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	null	1	16	75,648,316	75,648,365	+	1,569	AGO2_CLASH_Hejret2023	train
GAGAAAGGAGAAGGGAGTGATAGTAAGGAGAGTCCAAAAACCAAATCAGA	ACTGATTTCTTTTGGTGTTCAG	hsa-miR-29a-5p	mir-29	exon	1	5	154,792,685	154,792,734	+	3,580	AGO2_CLASH_Hejret2023	train
CCTAACCCTACTCCTAATCACATAACCTATTCCCCCGAGCAATCTCAATT	TGAGGTAGTAGGTTGTGTGGTT	hsa-let-7b-5p	let-7	exon	1	MT	14,124	14,173	+	825	AGO2_CLASH_Hejret2023	train
CAAACACCAAATAGTCCCTGTCCCCAGGAGCTCATAGTCTAGAGGTTAAC	CACTAGATTGTGAGCTCCTGGA	hsa-miR-28-3p	mir-28	intron	1	15	53,957,840	53,957,889	+	557	AGO2_CLASH_Hejret2023	train
GTAACTGCTTCTAGAGATGGGATTGTGAAGGTGTGGAAATAAAACCTACT	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr,exon	1	3	130,679,307	130,679,356	-	3,564	AGO2_CLASH_Hejret2023	train
AAACCAGATGTCTACAAGAGCCCTGCTTCAGATACTTACATAGTTTTTGG	AGTGGGGAACCCTTCCATGAGG	hsa-miR-491-5p	mir-491	exon	1	12	56,713,547	56,713,596	-	4,018	AGO2_CLASH_Hejret2023	train
TTTGTGTTAGACAGTTGAAACTGTTAGAGTTGGGGGCTCTGCTTTTTCCC	TAATGCCCCTAAAAATCCTTAT	hsa-miR-365a-3p	mir-365	three_prime_utr	1	12	56,596,628	56,596,677	-	3,623	AGO2_CLASH_Hejret2023	train
CCACACCCAGCTCAGGGGCCCAGACAGCAAGGACTCACCCAAAGACAGGG	GCCCCTGGGCCTATCCTAGAA	hsa-miR-331-3p	mir-331	exon	1	11	63,818,908	63,818,957	+	1,348	AGO2_CLASH_Hejret2023	train
TTTAGTTCTTCAAAGATAGGGAGGGAAGGGGGAACATGAGCCTTTGTTGC	TCAGGCTCAGTCCCCTCCCGAT	hsa-miR-484	mir-484	three_prime_utr	1	11	75,572,676	75,572,725	+	1,091	AGO2_CLASH_Hejret2023	train
ATACGAACAACAATTTTATTCAACCTAATGCCTTCCACACATTAACTTCT	TGAGGTAGTAGGTTGTGTGGTT	hsa-let-7b-5p	let-7	intron	1	21	34,093,650	34,093,699	-	827	AGO2_CLASH_Hejret2023	train
AAGGATCCTTTTCCACGGTGTGTTCTATGCCGGGGGCTTTGCCATTGTGT	TGAGGTAGTAGGTTGTATAGTT	hsa-let-7a-5p	let-7	exon	1	7	43,647,550	43,647,599	-	3,067	AGO2_CLASH_Hejret2023	train
GACCCTGGAGGAGTTCCTCGCATCCACTCAGAGGAAGGAGTTTGGGGACA	TCCCTGTCCTCCAGGAGCTCACG	hsa-miR-339-5p	mir-339	exon	1	19	48,919,220	48,919,269	+	2,805	AGO2_CLASH_Hejret2023	train
TATTTCTCTCTCCCCCAGCCGATGTTCTGAACCACCACCTGTAGCTAGGC	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	exon	1	X	108,733,125	108,733,174	-	3,348	AGO2_CLASH_Hejret2023	train
CTCCAGTAAGATACTACTTCAGTCATGACACTGATTAATACAAGTTGTCT	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	three_prime_utr,exon	1	4	67,618,985	67,619,034	-	1,848	AGO2_CLASH_Hejret2023	train
TCCTATAAGGCCCAGGAAGAGGGCAGAGGGGCCAGAAGGACTCCATGGCC	CTGGCCCTCTCTGCCCTTCCGT	hsa-miR-328-3p	mir-328	exon,three_prime_utr	1	7	151,143,936	151,143,985	+	2,511	AGO2_CLASH_Hejret2023	train
TGCGTCAGCAGCAATGTTTATGGTGAAAAATGGCAACGGGACCGCGTGCA	TAGCAGCACGTAAATATTGGCG	hsa-miR-16-5p	mir-15	exon	1	13	113,306,498	113,306,547	+	2,172	AGO2_CLASH_Hejret2023	train
GCCCACTGAGCCAAGAGCAGCAGGGAGCGTACAGGACGGGAGCAGCAGAT	TCAGGCTCAGTCCCCTCCCGAT	hsa-miR-484	mir-484	three_prime_utr	1	22	31,682,140	31,682,189	-	2,163	AGO2_CLASH_Hejret2023	train
CCCAGTTCGGGGCACAGTAGTCACCAATGATCGTTGGGGAGCTGGTAGCA	TCACCAGCCCTGTGTTCCCTAG	hsa-miR-1226-3p	mir-1226	exon	1	6	143,502,516	143,502,565	-	1,658	AGO2_CLASH_Hejret2023	train
CGGAGGAGCACCCAGTGCTGCTGACCGAGGCCCCCCTGAACCCCAAGGCC	GAGGGTTGGGTGGAGGCTCTCC	hsa-miR-296-3p	mir-296	exon	1	17	81,511,924	81,511,973	-	2,858	AGO2_CLASH_Hejret2023	train
TGTTTTAACTGTCCAGTGTTTGGATTTTACCTCTTGATAGCTCCATTTGT	CTCCGGGACGGCTGGGC	hsa-miR-4497	unknown	three_prime_utr	1	X	74,586,174	74,586,223	-	1,148	AGO2_CLASH_Hejret2023	train
GCTGCAAAGTTGGATAAGTGGAAATGTGGCTGCCCCTCTCCTCACTACTT	TAGCAGCACATCATGGTTTACA	hsa-miR-15b-5p	mir-15	three_prime_utr	1	2	149,023,849	149,023,898	+	4,034	AGO2_CLASH_Hejret2023	train
CATTATCTTGGCTGTGAGCTCCTTGGGTACGGGTACCTTGTATGTTTACT	AAGGAGCTCACAGTCTATTGAG	hsa-miR-28-5p	mir-28	intron	1	7	37,951,479	37,951,528	+	3,236	AGO2_CLASH_Hejret2023	train
CACTAAAATAATACAGCAATCCGTGGCCAGGGGAGCACCCCCTCCTGGTT	ACTGCCCTAAGTGCTCCTTCTGG	hsa-miR-18a-3p	mir-17	intron	1	7	102,252,202	102,252,251	+	674	AGO2_CLASH_Hejret2023	train
AAAAAAGAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA	TGAGGTAGTAGGTTGTATGGTT	hsa-let-7c-5p	let-7	null	1	17	22,044,120	22,044,169	-	201	AGO2_CLASH_Hejret2023	train
GCTGTACTGCGAAACCCACGCAAGAGCCCGCACAAAGCCCCCAGAGGGCT	TGCGGGGCTAGGGCTAACAGCA	hsa-miR-744-5p	mir-744	exon	1	4	185,502,326	185,502,375	-	2,264	AGO2_CLASH_Hejret2023	train
GGACCAGTTTAAAAAGACTAACGCATTTGTCCTCGTTGTTGGGTGTTTTT	CAAAGTGCTTACAGTGCAGGTAG	hsa-miR-17-5p	mir-17	three_prime_utr	1	17	10,675,742	10,675,791	-	567	AGO2_CLASH_Hejret2023	train
GGCCTAGACAAAGAAGTCTCCTATAACTGGGACCCCAAAGATGCAGCTTC	TGGCGGCGGTAGTTATGGGCTT	hsa-miR-4467	unknown	exon	1	X	108,733,778	108,733,827	-	2,105	AGO2_CLASH_Hejret2023	train
AACAAAAGTTGGTCTTAAGCTTCCACCTTGAGCAGCCTTGGAAACCTAAC	TGGAAGACTAGTGATTTTGTTGTT	hsa-miR-7-5p	mir-7	three_prime_utr	1	18	31,548,653	31,548,702	+	3,840	AGO2_CLASH_Hejret2023	train
TGTGTGGTAAAGGGCCAAAGTCAATAATTGGGACAAATGGTAAAGATGAT	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	three_prime_utr	1	12	27,798,462	27,798,511	+	2,559	AGO2_CLASH_Hejret2023	train
AGATTATTAGACTATAATAAGGATGAAATTGCTGTCTGTAATTTTGTTGA	CAAAGTGCTTACAGTGCAGGTAG	hsa-miR-17-5p	mir-17	three_prime_utr	1	8	43,022,797	43,022,846	+	2,210	AGO2_CLASH_Hejret2023	train
GAGTCTTTCAGGACCTGGACAGTGAAGGGAGCCCGGGCAGCCACCGTCTC	TCCGAGCCTGGGTCTCCCTCTT	hsa-miR-615-3p	mir-615	three_prime_utr,exon	1	12	110,435,130	110,435,179	-	1,631	AGO2_CLASH_Hejret2023	train
TATTAACGATCTTTTAAAAGAATCCTCCTTTTGGGCATCTGCCCTCCCAC	TCCGAGCCTGGGTCTCCCTCTT	hsa-miR-615-3p	mir-615	intron	1	12	95,385,670	95,385,719	-	264	AGO2_CLASH_Hejret2023	train
GTTTATATGCACTTTCTTCCGATCTGTACCTGAGAGGTTTGTGGAAAAGA	TGAGGTAGTAGGTTGTATAGTT	hsa-let-7a-5p	let-7	three_prime_utr	1	12	109,597,179	109,597,228	+	1,369	AGO2_CLASH_Hejret2023	train
GGCCTCATCTCTGAGAGGATCTCCTGGGTCTTGGTTCAAGGGTTAGGAAA	TACCCTGTAGATCCGAATTTGTG	hsa-miR-10a-5p	mir-10	intron	1	4	3,406,686	3,406,735	-	389	AGO2_CLASH_Hejret2023	train
TCTCTCAAAGTGTGGAGGAGACGTTGCCGTCAGGCGGGAGCCAAGTGCCG	AACATTCAACGCTGTCGGTGAGT	hsa-miR-181a-5p	mir-181	three_prime_utr	1	7	151,556,384	151,556,433	-	2,355	AGO2_CLASH_Hejret2023	train
GTGTCTAGGTGCCTGGCACCCGACCCTGACTAAAACAGCTGAAAACAGTT	TCCAGCATCAGTGATTTTGTTG	hsa-miR-338-3p	mir-338	three_prime_utr	1	14	105,141,443	105,141,492	-	294	AGO2_CLASH_Hejret2023	train
TTCTTACTCGTGCATCAGGTCCTGGTCTGTGTCAGGCCCAGGGGACACAG	GCCCCTGGGCCTATCCTAGAA	hsa-miR-331-3p	mir-331	three_prime_utr	1	19	29,700,168	29,700,217	-	2,836	AGO2_CLASH_Hejret2023	train
AGAGGGAGTTGGAGAGCAAACTTCAGAGGCTACAGGCTCAGGGTATCCAA	TCCGAGCCTGGGTCTCCCTCTT	hsa-miR-615-3p	mir-615	exon	1	3	132,719,046	132,719,095	-	4,000	AGO2_CLASH_Hejret2023	train
CCCAGTGGTGCCTCAACCGAGCTTCCAAGCTCTTTCCACTTTGGCTGGGT	TAAAGTGCTTATAGTGCAGGTAG	hsa-miR-20a-5p	mir-17	null	1	10	39,114,414	39,114,463	-	2,571	AGO2_CLASH_Hejret2023	train
CCTCGCCTTTCAAGCACGCGGACATCGTCACCACCACTACTCACAAGACT	TGAGGTAGTAGGTTGTGTGGTT	hsa-let-7b-5p	let-7	exon	1	12	57,232,780	57,232,829	+	90	AGO2_CLASH_Hejret2023	train
CTACCGCGGCCGAGCGCGCCGGCCACCGCCTGCACCGCCCTTCCGCCCGC	ACTCGGCGTGGCGTCGGTCGTG	hsa-miR-1307-3p	mir-1307	intron	1	12	6,766,418	6,766,467	+	1,875	AGO2_CLASH_Hejret2023	train
TAACATATTCACTGGTTCCAGGGATTTGGGCATGGACTTCTGTAGGTGGC	TACCCTGTAGAACCGAATTTGTG	hsa-miR-10b-5p	mir-10	three_prime_utr	1	15	55,614,890	55,614,939	-	4,049	AGO2_CLASH_Hejret2023	train
TTCGCTCTTTCGTGCCGCCCCTCAAGCCTCTTAATTTAGGGATGGACACG	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	null	1	6	43,369,922	43,369,971	+	1,422	AGO2_CLASH_Hejret2023	train
CCCTACCTTACCCCTCTGCCCCTAGCCAAGGAGTGTGAATTTATAGATCT	TGAGGGGCAGAGAGCGAGACTTT	hsa-miR-423-5p	mir-423	three_prime_utr	1	X	153,696,028	153,696,077	+	2,041	AGO2_CLASH_Hejret2023	train
GGCTCCATTTTACTTGTTTGATGAAATTGACCAGGCTCTGGATGCTCAGC	TCCGAGCCTGGGTCTCCCTCTT	hsa-miR-615-3p	mir-615	exon	1	10	110,602,935	110,602,984	+	2,993	AGO2_CLASH_Hejret2023	train
ATACTCCTACTTTCTACCAAACTCTGGCTGGAGTCACACATTGTAAGTAA	GCTGACTCCTAGTCCAGGGCTC	hsa-miR-345-5p	mir-345	intron,exon	1	17	60,288,515	60,288,564	-	436	AGO2_CLASH_Hejret2023	train
TCCGCCTCTTGGGTTAAAAGAATTCTCCTGCCTCAGCCTCCTGAGTAGCT	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr	1	14	73,716,568	73,716,617	-	3,907	AGO2_CLASH_Hejret2023	train
AGGGATGGGGAGAAGGTTCTGGATCTCTGTGCTGCTCCTGGAGGGAAATC	TAGCAGCACGTAAATATTGGCG	hsa-miR-16-5p	mir-15	exon	1	3	94,084,372	94,084,421	+	3,248	AGO2_CLASH_Hejret2023	train
GCCTCCTCAGCCCAGGGCTGAGTTTTAAGATTTTCTCTCCTTTCCTCTTC	GCCCCTGGGCCTATCCTAGAA	hsa-miR-331-3p	mir-331	three_prime_utr	1	17	63,589,369	63,589,418	+	2,190	AGO2_CLASH_Hejret2023	train
CTAATCAGCAAGTCCAGTGGCCACTTAGAGCCCAGCTCCTACCTCTTCAT	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr	1	16	23,465,305	23,465,354	-	3,806	AGO2_CLASH_Hejret2023	train
TTTCTCCCCAGCTTAGTCCACAACTTGTAAGGCAACAAATAGCCATGGCC	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	exon	1	2	199,348,932	199,348,981	-	3,710	AGO2_CLASH_Hejret2023	train
CGCTATGGGTGTGAGTGGAAGAGAGGGAGACTTTTTTACCTGGGGTTGGT	AGCTCGGTCTGAGGCCCCTCAGT	hsa-miR-423-3p	mir-423	three_prime_utr	1	14	94,051,055	94,051,104	+	638	AGO2_CLASH_Hejret2023	train
ATCATACAGTGTCTAAGTCTGTTTGTGGTGCTGTAACAAAATACCTGAGA	TAGCACCATCTGAAATCGGTTA	hsa-miR-29a-3p	mir-29	null	1	8	43,130,553	43,130,602	+	901	AGO2_CLASH_Hejret2023	train
GATTGTTAAAACTTGTTTGTAATGGGTTGGTGCAAAAGTAATTGTGGTTT	CAAAAACCGCAATTACTTTTGCA	hsa-miR-548h-3p	mir-548	three_prime_utr	1	13	30,206,666	30,206,715	-	3,479	AGO2_CLASH_Hejret2023	train
GCTGGTTGGCAAATATTTCCATCTTTCACTATTAGCAAGAGTGCCTTATA	TCACAGTGAACCGGTCTCTTT	hsa-miR-128-3p	mir-128	intron	1	7	3,452,592	3,452,641	-	1,493	AGO2_CLASH_Hejret2023	train
CCTGTCCAGGTAATCAAAGACCTAAAGGGCTCGGACTACAGCTGGTCCTA	TCCGAGCCTGGGTCTCCCTCTT	hsa-miR-615-3p	mir-615	exon,intron	1	16	70,676,938	70,676,987	-	1,832	AGO2_CLASH_Hejret2023	train
TAGCCACTACACACTGAATGTCCGAGTGGTCAATGGGAAAGGGGAGGGCC	TCAGGCTCAGTCCCCTCCCGAT	hsa-miR-484	mir-484	exon	1	7	108,180,262	108,180,311	-	1,488	AGO2_CLASH_Hejret2023	train
CAAAAAGGAGCCTGTGAGAGGCAGAGAGCGGGAATTTCAGGAAATGGCCT	AGCTCGGTCTGAGGCCCCTCAGT	hsa-miR-423-3p	mir-423	intron	1	14	76,012,418	76,012,467	-	639	AGO2_CLASH_Hejret2023	train
ACCCCTATAAGCACATTAAATACTACTTTGCCGTGACAGCTCAGTGTACT	CACACACACACACACACGTAT	hsa-miR-8485	unknown	intron	1	21	33,577,701	33,577,750	+	710	AGO2_CLASH_Hejret2023	train
GGTGATAGACTGAAGCCAGAACAGTGCCACACCCTCGCCTTAATTCCTTG	TGAGGTAGTAGGTTGTATAGTT	hsa-let-7b-5p	let-7	three_prime_utr	1	20	3,870,422	3,870,471	+	47	AGO2_CLASH_Hejret2023	train
ATGTGAAGTGAGGGCAGCCTTGTGCAGGGCTATGAAGTTTGGCCTAACTC	AGCTTCTTTACAGTGCTGCCTTG	hsa-miR-103a-2-5p	mir-103	null	1	13	21,917,763	21,917,812	+	628	AGO2_CLASH_Hejret2023	train
TGCTCCTGCCGCTCCCGCTGCCGCGCCTCCTGCGGAGAAGGCCCCTGTAA	TGAGGGGCAGAGAGCGAGACTTT	hsa-miR-423-5p	mir-423	exon	1	6	26,056,368	26,056,417	-	3,566	AGO2_CLASH_Hejret2023	train
GCACATGCCACAGCTCCTGTGAATATTGCCGGCTCCAGAACCGCCGCAGC	TAGCAGCACATAATGGTTTGTG	hsa-miR-15a-5p	mir-15	exon	1	16	2,767,558	2,767,607	+	3,406	AGO2_CLASH_Hejret2023	train
AGGGTGGAAATTTAATGAGTCAGGCCCGTGGGGATGTAGCAGGAGGCCTG	CGCATCCCCTAGGGCATTGGTG	hsa-miR-324-5p	mir-324	exon	1	3	57,249,410	57,249,459	+	928	AGO2_CLASH_Hejret2023	train
GCAGGCGCGGAGCTAGACCTCGCTGCAGCCCCCATCGCCTCGGGGAGTCT	TGAGGGGCAGAGAGCGAGACTTT	hsa-miR-423-5p	mir-423	five_prime_utr	1	10	102,504,015	102,504,064	+	1,265	AGO2_CLASH_Hejret2023	train
GTGCCATGGCCTCCGTCTCCAAGCTCGCCTGCATCTACTCGGCCCTCATT	AGCTCGGTCTGAGGCCCCTCAGT	hsa-miR-423-3p	mir-423	exon	1	2	176,201,208	176,201,257	-	114	AGO2_CLASH_Hejret2023	train
GGAATTAGCAGCCCATCTCCCATTAACGCTTTTCTTTCTGTTGACCACCT	AAAAGCTGGGTTGAGAGGGCAA	hsa-miR-320d	mir-320	null	1	16	24,823,733	24,823,782	+	104	AGO2_CLASH_Hejret2023	train
CTTCTGTGAAACATGGCGGTAGGCTGGGACCATAACACAAGGTAAAATAC	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	intron,five_prime_utr	1	12	29,381,106	29,381,155	-	1,666	AGO2_CLASH_Hejret2023	train
TGTTCCACTGCCCCTCCTCCTCACCCTATCACCCATGGATCGTAATGTAA	TGGAGAGAAAGGCAGTTCCTGA	hsa-miR-185-5p	mir-185	three_prime_utr	1	17	42,843,134	42,843,183	+	3,354	AGO2_CLASH_Hejret2023	train
GTGGTGTAAAACACTAGAACTTATTCCTCCTACCTGCCTGTATTTCTGTA	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr	1	19	44,132,922	44,132,971	+	2,394	AGO2_CLASH_Hejret2023	train
GAGACAGAAGCCCGGAAATACGTTCGCAAGTGAGGGGAGCCTGAATACTG	TCAGGCTCAGTCCCCTCCCGAT	hsa-miR-484	mir-484	exon	1	7	73,683,776	73,683,825	+	4,148	AGO2_CLASH_Hejret2023	train
AAATGCAATCTCCCCTTGATTTAAACACACAGATACACACACACACACAC	TGAGGTAGTAGGTTGTGTGGTT	hsa-let-7b-5p	let-7	three_prime_utr	1	11	69,652,746	69,652,795	+	4,176	AGO2_CLASH_Hejret2023	train
TCTTCACAGGTGTAACCTGGCCAGTGTGATGCTTCAGCTTCTAGCAATGA	ATCACATTGCCAGGGATTTCC	hsa-miR-23a-3p	mir-23	exon,intron	1	17	5,453,628	5,453,677	-	1,176	AGO2_CLASH_Hejret2023	train
GTTGGTTTTTATTTTTGGGGGGAATGACATGTTTGGGTCTTTTATACATG	AAGGCCCGGGCTTTCCTCCCAG	hsa-miR-4747-3p	unknown	null	1	21	34,788,830	34,788,879	-	3,700	AGO2_CLASH_Hejret2023	train
CTTCTTATGTATTTTCAAGATTATTCTGTGCACTTTAAATTTACTTAACT	TAAAGTGCTGACAGTGCAGAT	hsa-miR-106b-5p	mir-17	three_prime_utr	1	6	47,232,410	47,232,459	-	1,683	AGO2_CLASH_Hejret2023	train
CATATAGAGTATATGCCAAGAACACTACCATATATGGCATCAGCTTTGGT	AATGTGGAAGTGGTCTGAGGCAT	hsa-miR-4657	mir-4657	three_prime_utr	1	7	44,881,731	44,881,780	-	3,209	AGO2_CLASH_Hejret2023	train
TGGTTTCAAGATGTCTGGCCGCGGTAAGGGCGGAAAGGGTCTAGGTAAGG	CTGGCCCTCTCTGCCCTTCCGT	hsa-miR-328-3p	mir-328	exon	1	6	26,189,037	26,189,086	-	1,591	AGO2_CLASH_Hejret2023	train
CTGCTATAGTGGAGGCCGGAGCAGGAACAGGTTGAACAGTCTACCCTCCC	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	exon	1	MT	6,247	6,296	+	3,835	AGO2_CLASH_Hejret2023	train
CTGTCTCTGTAATCCCTCCTACCATTAAGAAAAACTTATTTCTTAGACAT	TGAGGTAGGAGGTTGTATAGTT	hsa-let-7e-5p	let-7	three_prime_utr	1	21	34,097,752	34,097,801	+	3,695	AGO2_CLASH_Hejret2023	train
CATTGTTCCATTACCTTGAATGTTGGAAAGATATGATACGTGCTGCTTGT	TAGCAGCACGTAAATATTGGCG	hsa-miR-16-5p	mir-15	three_prime_utr	1	8	41,510,258	41,510,307	+	4,044	AGO2_CLASH_Hejret2023	train
CTACTGAAGTCCTAAAGAGCAACCCTAACTCAAGCCATTGGCACACAGGC	TTGTGCTTGATCTAACCATGT	hsa-miR-218-5p	mir-218	intron	1	15	26,645,515	26,645,564	+	119	AGO2_CLASH_Hejret2023	train
GTACAGTGACAACCCGGGCCGGCAGCAAGGACACAGATGCAGCCACAGTA	TATTGCACTTGTCCCGGCCTGT	hsa-miR-92a-3p	mir-25	three_prime_utr	1	15	80,596,792	80,596,841	+	553	AGO2_CLASH_Hejret2023	train
CTCTTTTTCAGTTGGGATGAATGGGTTCCGGAGAGCAGAGTACTCAAATA	CTCCTGGGGCCCGCACTCTCGC	hsa-miR-1343-3p	mir-1343	intron,exon	1	15	78,886,130	78,886,179	+	484	AGO2_CLASH_Hejret2023	train
AAAAGGAGCCTAACTGCATTATGAGAACAGAAAGAATATTTTAATAACCA	TAAAGTGCTTATAGTGCAGGTAG	hsa-miR-20a-5p	mir-17	null	1	15	52,890,523	52,890,572	+	744	AGO2_CLASH_Hejret2023	train
AAAAGTAGAGCGATTTTCAGGAGAAAAAAGTCGTGGGGACTGAGTTCAGG	TCAGGCTCAGTCCCCTCCCGAT	hsa-miR-484	mir-484	three_prime_utr	1	4	95,165,224	95,165,273	-	1,689	AGO2_CLASH_Hejret2023	train
CTTACCCTTCCCTGCCTCTAGAGCCACTGTTCTCACTACTTCTAAGAAAT	TTGGAGGCGTGGGTTTT	hsa-miR-4443	unknown	three_prime_utr	1	19	44,067,544	44,067,593	+	124	AGO2_CLASH_Hejret2023	train
TTTAATTTTTTTCCCTCAAACCACCCAGCTCCTTACATAGTTTTTAATTA	AAAAGCTGGGTTGAGAGGGCGA	hsa-miR-320a-3p	mir-320	three_prime_utr	1	9	125,148,038	125,148,087	-	4,016	AGO2_CLASH_Hejret2023	train

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GeoTarget-RNA: Massive Genomic Interactions Dataset

This dataset contains the training, validation, and testing cohorts used for the GeoTarget-RNA thesis project. It provides large-scale, experimentally validated miRNA-mRNA interactions with proper genomic negatives.

The Synthetic Bias Problem (Why this dataset was built)

Early versions of this project (and many legacy machine learning models in literature) constructed negative interactions by artificially shuffling sequences or randomly pairing genes. We discovered a critical flaw with this approach: Evolutionary Conservation Data Leaks. When using synthetic negatives that don't correspond to real 3'UTR loci, tools like PhyloP return a conservation score of 0.0. The model learns to completely ignore biophysics and instead relies on the heuristic: "If conservation is 0.0, it must be a synthetic negative."

To solve this, we pivoted to miRBench, extracting debiased AGO2 CLASH and eCLIP datasets. The negatives in this dataset are real 3'UTR loci that AGO2 was experimentally proven not to bind. This forces the model to actually learn biophysics rather than sequence-level artifacts.

Dataset Structure

`v26_massive_genomic_dataset.csv`

Size: 573,656 interactions (98MB compressed)
Source: AGO2 CLASH (Hejret 2023) and eCLIP (Manakov 2022) protocols.
Columns:
- miRNA_Sequence: The mature miRNA sequence.
- Full_3UTR_Sequence: The target 3'UTR sequence.
- Label: 1 (Binding) or 0 (Non-binding).
- (And other metadata columns for IDs and transcript loci).

`external_benchmarks/mirtarbase_v10.csv`

5,000 strong-evidence test interactions extracted from miRTarBase 10.0 for pure external validation.

`external_benchmarks/encori_pdcd4.csv`

A specific subset of interactions derived from ENCORI CLIP-seq experiments on the PDCD4 RBP, used for multi-omics validation.

How to use

from datasets import load_dataset

dataset = load_dataset("reogine/Massive-Genomic-Interactions")
print(dataset)

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Models trained or fine-tuned on reogine/Massive-Genomic-Interactions

reogine/GeoTarget-RNA-6D-Vital

Updated 16 days ago