Sing a plant growth strategy. Field Crops Res 118: 112. five. Shekoofa A, Emam Y, Pessarakli M Impact of partial defoliation right after silking stage on yield and yield components of three grain maize hybrids under semi-arid circumstances. Arch Agron Soil Sci 7: 777788 6. Shekoofa A, Emam Y, Pessarakli M Source-sink manipulation effects on maize buy KS 176 kernel high-quality, In Annual meetings “Fundamental for Life: Soil, Crop, and Environmental Sciences” San Antonio, USA. 7. Hsiao HW, Tasi MS, Wang SC Spatial data mining of colocation patterns for selection support in agriculture. Asian Journal of Overall health and Info Sci 1: 6172. 8. Shekoofa A, Emam Y, Ebrahimi M, Ebrahimie E Application of supervised feature selection procedures to define probably the most significant traits affecting maximum kernel water content material in maize. Aust J Crop Sci 5: 162168. 9. Roddick JF, Hornsby K, Spiliopoulou M An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Analysis. Lecture Notes in Personal computer Science 2007: 147163. 10. Elson A, Tailor S, Salim RB, Hillaby K, Jurkovic D Expectant management of tubal ectopic pregnancy: prediction of profitable outcome working with choice tree analysis, Ultrasound Obstet Gynecol 6: 552556. 11. Schuize FH, Wolf H, Jansen H, Vander VP Applications of artificial neural networks in integrated water management: fiction or future Water Sci Technol 52: 2131. 12. Ebrahimi M, Ebrahimie E Sequence-Based Prediction of Enzyme Thermostability By way of Bioinformatics Algorithms. Curr Bioinform 5: 195 203. 13. Ebrahimi M, Lakizadeh A, Agha-Golzadeh P, Ebrahimie E, Ebrahimi 
M Prediction of Thermostability from Amino Acid Attributes by Mixture of Clustering with Attribute Weighting: A new Vista in Engineering Enzymes. PLoS 1379592 1 six: e23146. 14. Ashrafi E, Alemzadeh A, Ebrahimi M, Ebrahimie E, Dadkhodaei N Amino Acid Attributes of P1B-ATPase Heavy Metal Transporters Enabling Small Numbers of Organisms to Cope with Heavy Metal Pollution. Bioinform Biol Insights 5: 5982. 15. Ye X, Fu Z, Wang H, Du W, Wang R, et al A computerized program for signal detection in spontaneous reporting method of Shanghai China. Pharmacoepidemiol Drug Saf. 18: 154158. 16. Gromiha MM, Yabuki Y Functional discrimination of membrane proteins making use of machine studying tactics. BMC Bioinformatics 9: 135. 17. Thai KM, Ecker GF Similarity-based SIBAR descriptors for classification of chemically diverse hERG blockers. Mol Divers 13: 321336. 18. Shekoofa A, Emam Y, Ebrahimi M, Ebrahimie E Defining the key traits of maize yield elements contributing maximum kernel water content by way of screening, clustering, and selection tree algorithms. 11th Asian Maize Conference. Nov. 7-11, Chima. 19. Dancey D, Bandar XA, McLean D Logistic model tree extraction from artificial neural networks, IEEE Transactions on Systems, Man, and Cybernetics, Aspect B: Cybernetics, 37: 
50-14-6 site 794802. 20. Wang YY, Li J Feature-selection ability from the decision-tree algorithm as well as the effect of feature-selection/extraction on decision-tree benefits based on hyperspectral data. Int J Rem Sen. 29: 29933010. 21. Shekoofa A Kernel water content and final dry weight of maize crop as impacted by source/sink ratio, Ph.D. diss. Shiraz Univ., Shiraz, Iran. 22. Sala RG, Westgate ME Andrade FH Source/sink ratio and the partnership amongst maximum water content, maximum volume and final dry weight of maize kernels. Field Crops Res 101: 1925. 23. Gambin BL, Borras L, Otegui ME Sourcesink relations and kernel weight differences in maize temperate hy.Sing a plant growth method. Field Crops Res 118: 112. five. Shekoofa A, Emam Y, Pessarakli M Impact of partial defoliation just after silking stage on yield and yield components of 3 grain maize hybrids under semi-arid conditions. Arch Agron Soil Sci 7: 777788 six. Shekoofa A, Emam Y, Pessarakli M Source-sink manipulation effects on maize kernel high quality, In Annual meetings “Fundamental for Life: Soil, Crop, and Environmental Sciences” San Antonio, USA. 7. Hsiao HW, Tasi MS, Wang SC Spatial data mining of colocation patterns for selection support in agriculture. Asian Journal of Overall health and Info Sci 1: 6172. eight. Shekoofa A, Emam Y, Ebrahimi M, Ebrahimie E Application of supervised feature selection methods to define one of the most important traits affecting maximum kernel water content in maize. Aust J Crop Sci 5: 162168. 9. Roddick JF, Hornsby K, Spiliopoulou M An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Investigation. Lecture Notes in Laptop or computer Science 2007: 147163. ten. Elson A, Tailor S, Salim RB, Hillaby K, Jurkovic D Expectant management of tubal ectopic pregnancy: prediction of thriving outcome using choice tree evaluation, Ultrasound Obstet Gynecol six: 552556. 11. Schuize FH, Wolf H, Jansen H, Vander VP Applications of artificial neural networks in integrated water management: fiction or future Water Sci Technol 52: 2131. 12. Ebrahimi M, Ebrahimie E Sequence-Based Prediction of Enzyme Thermostability Via Bioinformatics Algorithms. Curr Bioinform five: 195 203. 13. Ebrahimi M, Lakizadeh A, Agha-Golzadeh P, Ebrahimie E, Ebrahimi M Prediction of Thermostability from Amino Acid Attributes by Mixture of Clustering with Attribute Weighting: A brand new Vista in Engineering Enzymes. PLoS 1379592 One particular six: e23146. 14. Ashrafi E, Alemzadeh A, Ebrahimi M, Ebrahimie E, Dadkhodaei N Amino Acid Capabilities of P1B-ATPase Heavy Metal Transporters Enabling Little Numbers of Organisms to Cope with Heavy Metal Pollution. Bioinform Biol Insights five: 5982. 15. Ye X, Fu Z, Wang H, Du W, Wang R, et al A computerized method for signal detection in spontaneous reporting system of Shanghai China. Pharmacoepidemiol Drug Saf. 18: 154158. 16. Gromiha MM, Yabuki Y Functional discrimination of membrane proteins working with machine mastering methods. BMC Bioinformatics 9: 135. 17. Thai KM, Ecker GF Similarity-based SIBAR descriptors for classification of chemically diverse hERG blockers. Mol Divers 13: 321336. 18. Shekoofa A, Emam Y, Ebrahimi M, Ebrahimie E Defining the principle traits of maize yield elements contributing maximum kernel water content through screening, clustering, and selection tree algorithms. 11th Asian Maize Conference. Nov. 7-11, Chima. 19. Dancey D, Bandar XA, McLean D Logistic model tree extraction from artificial neural networks, IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 37: 794802. 20. Wang YY, Li J Feature-selection capability on the decision-tree algorithm and the impact of feature-selection/extraction on decision-tree outcomes determined by hyperspectral data. Int J Rem Sen. 29: 29933010. 21. Shekoofa A Kernel water content material and final dry weight of maize crop as affected by source/sink ratio, Ph.D. diss. Shiraz Univ., Shiraz, Iran. 22. Sala RG, Westgate ME Andrade FH Source/sink ratio along with the relationship amongst maximum water content material, maximum volume and final dry weight of maize kernels. Field Crops Res 101: 1925. 23. Gambin BL, Borras L, Otegui ME Sourcesink relations and kernel weight variations in maize temperate hy.
