{"id":"W4232894656","doi":"10.4018/978-1-60960-491-2.ch007","title":"Biclustering of DNA Microarray Data","year":2011,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Biclustering; Computer science; Identification (biology); Microarray analysis techniques; Computational biology; Data mining; Biological data; Microarray databases; Cluster analysis; Microarray; Bioinformatics; Artificial intelligence; Gene; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002198726,0.001213586,0.00171905,0.00276837,0.0005080953,0.001402374,0.001171967,0.0006725582,0.00323115],"category_scores_gemma":[0.007800381,0.0007046386,0.001417258,0.00313424,0.0007481681,0.001090594,0.001518152,0.001613112,0.002681492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005222614,"about_ca_system_score_gemma":0.0005628051,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009229396,"about_ca_topic_score_gemma":0.001242742,"domain_scores_codex":[0.9976019,0.0009489013,0.0001902113,0.0004958986,0.0006683454,0.0000947745],"domain_scores_gemma":[0.9967272,0.002151427,0.0001743544,0.0003767733,0.0005035965,0.00006665277],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004127344,0.00008872777,0.002964282,0.002237362,0.0005892104,0.0003985957,0.0006007623,0.1622657,0.03437619,0.04183379,0.04721542,0.7070172],"study_design_scores_gemma":[0.00003843554,0.0001440598,0.002591049,0.0002704037,0.0000996085,0.0007627688,0.0002699739,0.8309375,0.01573256,0.1036988,0.0453416,0.0001132231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00458777,0.002883208,0.98827,0.0003023748,0.0001948389,0.0001060961,0.0009982861,0.00132762,0.001329724],"genre_scores_gemma":[0.06833271,0.005613792,0.9108453,0.0007284288,0.0002927494,0.0009420974,0.008040262,0.0006865248,0.004518084],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00323115,"threshold_uncertainty_score":0.01162809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04400898701187462,"score_gpt":0.2701675585442981,"score_spread":0.2261585715324235,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}