Table 1.

A comprehensive list of the reviewed methods/tools for the prediction of prokaryotic promoters^a

Framework	Toolb	Year	Webserver/toolc	Features/Motifs	Scoring function /Algorithm	Evaluation strategy	Promoter typed	Speciese	Sequence length (bp)f
Deep learning–based	Le et al. [67]	2019	Yes*	FastText n-grams	CNN	5-fold CV	Strong and weak; and unknow	E. coli	81
	iPromoter-BnCNN [70]	2020	Decommissioned	Monomer, trimer and DSP	CNN	5-fold CV and independent test	, , , , and	E. coli	81
Traditional machine learning–based	Leo Gordon et al. [33]	2003	Decommissioned	SAK	SVM	50% train, 50% test	σ  70	E. coli	80
	Monteiro et al. [36]	2005	No	–	Comparative study of NBC, DT, SVM and ANN	Leave-one-out	–	B. subtilis and E. coli	117, 57
	da Silva et al. [38]	2006	No	–	Comparative study of KNN, NBC, DT, SVM and ANN	10-fold CV	–	B. subtilis, B. licheniformis, B. cereus, B. megaterium, B. thuringiensis, and B. firmus	111
	Wang et al. [40]	2006	No	DSP1, −10 motif scores	Fisher LDA	Independent test	–	E. coli and B. subtilis	100
	J. J. Gordon et al. [41]	2006	Decommissioned	5-mer tagged with its location, −10 and −35 hexamers	committee-SVM	10-fold CV	σ  70	E. coli	200
	Towsey et al.-I [42]	2006	No	5-mer tagged with its location, −10 and −35 hexamers	SVM	10-fold CV	σ  70	E. coli	200
	pHMM-ANN [39]	2007	No	UP element, −10, −35 elements pHMMs	ANN	Independent test	–	E. coli	–
	Towsey et al.-II [44]	2007	No	Similarity score of candidate TSS, −10, −35 scores, TSS-GSS distance, DSP2	C4.5	10-fold CV	σ  70	E. coli	250
	TSS-PREDICT [47]	2008	No	−10 and −35 hexamers, 5-mer tagged with its location, TSS- GSS distribution	Ensemble-SVM	Independent test	σ  70; σ43; σ66	E. coli, B. subtilis and C. trachomatis	200
	N4 [48]	2009	No	DDS	ANN	Leave-one-out	–	E. coli	414
	Polat et al. [49]	2009	No	57 sequential DNA nucleotide attributes	Fuzzy-AIRS	10-fold CV	–	E. coli	57
	Song et al. [53]	2012	Yes*	vw Z-curve	PLS	10-fold CV	, , , , and ; , , etc.	E. coli and B. subtilis	80
	iPro54-PseKNC [55]	2014	Yes*	PseKNC	SVM	10-fold CV and leave-one-out	σ  54	E. coli	81
	de Avila e Silva et al. [56]	2014	No	DDS	ANN	2,3,10-fold CV	, , , , and	E. coli	80
	bTSSfinder [57]	2017	Decommissioned	PE, DPE, k-mer, TFBSD, PCP	ANN	Independent test	, , , , , and	E. coli, S. elongatus, Nostoc, and Synechocystis	251, 1101
	iPromoter-2L [58]	2018	Yes	PseKNC	RF	5-fold CV	, , , , and	E. coli	81
	70ProPred [59]	2018	Yes	PSTNPSS/PSTNPDS, PseEIIP	SVM	5-fold CV and leave-one-out	σ  70	E. coli	81
	IBPP-SVM [60]	2018	Yes*	‘image’	SVM	Independent test	σ  70	E. coli	81
	BacSVM+ [61]	2018	Decommissioned	–	SVM	–	, , , , and	B. subtilis	80
	iPro70-PseZNC [62]	2019	Yes	PseZNC	SVM	5-fold CV	σ  70	E. coli	81
	iPromoter-FSEn [63]	2019	Yes	k-mer, g-gapped k-mer, NSM, ASPC, PSO, DN	SVM, LDA, LR	10-fold CV and leave-one-out	σ  70	E. coli	81
	iPro70-FMWin [64]	2019	Yes	k-mer, g-gapped k-mer, NSM, ASPC, PSO	LR	10-fold CV	σ  70	E. coli	81
	iPSW(2L)-PseKNC [65]	2019	Yes	General PseKNC	SVM	5-fold CV	Strong and weak; and unknow	E. coli	81
	MULTiPly [66]	2019	Yes	BPB, KNN, KNC, DAC	SVM	5-fold CV, leave-one-out and independent test	, , , , and	E. coli	81
	iPromoter-2L2.0 [68]	2019	Yes	k-mer, PseKNC	SVM, EL	5-fold CV	, , , , and	E. coli	81
	SELECTOR [69]	2020	Yes	CKSNAP, PCPseDNC, PSTNPss and DNA strand	RF, AdaBoost, GBDT, LightGBM, XGBoost	5-fold CV and independent test	, , , , and	E. coli	81
Scoring function–based	Huerta et al. [34]	2003	No	−10 and −35 box, spacer between −10 and −35 box	PWM	Independent test	σ  70	E. coli	250
	TLS-NNPP [35]	2005	No	TSS-TLS distance, the results from NNPP2.2	Probability	Independent test	–	E. coli	500
	Kanhere et al. [37]	2005	No	DDS	DE	Independent test	–	E. coli, B. subtilis and C. glutamicum	1000
	Li et al. [43]	2006	No	Hexamer sequence conservation	PCSF	10-fold CV	σ  70	E. coli	81
	Beagle [72]	2006	Decommissioned	UP element, −10, −35 and extended −10 elements, and TSS-GSS gap	PWM	10-fold CV	σ  70	E. coli and B. subtilis	250
	Footy [45]	2007	Decommissioned	−10 and −35 hexamers	PWM	Independent test	σ  66	C. trachomatis, C. pneumoniae, C. caviae and C. muridarum	–
	Rangannan et al. [46]	2007	No	DDS	DE	Independent test	–	E. coli and B. subtilis	101, 1001
	PromPredict [50]	2009	Yes*	DDS	DE	Independent test	–	E. coli, B. subtilis and M. tuberculosis	1001
	PromPredict [51]	2010	Yes*	DDS, GC content	DE	Independent test	–	913 bacteria in PromBase [183]	1001
	BacPP [52]	2011	Yes	Rules extracted from neural networks	Weighting promoter prototypes	2, 3, 10-fold CV	, , , , and	E. coli	80
	Todt et al. [54]	2012	No	−10, −35 and extended −10 elements	PWM	Independent test	σ  70	L. plantarum	100
	G4PromFinder [71]	2018	Yes*	AT-rich element and G-quadruplex motif	–	Independent test	–	S. coelicolor and P. aeruginosa	251

^aAbbreviations: CNN—convolutional neural network; CV—cross-validation; DSP—DNA structural property; SAK—sequence alignment kernel; SVM—support vector machine; TSS-TLS distance—the distance between the transcription start site (TSS) and the translation start site (TLS); TDNN—time-delay neural network; NBC—naïve Bayes classifier; DT—decision tree; ANN—artificial neural network; KNN—k-nearest neighbor; DSP₁—SIDD, curvature, deformability, thermodynamic stability; SIDD—stress-induced DNA duplex destabilization; LDA—linear discriminant analysis; committee-SVM—DGS, PWM and ensemble SVM; DGS—the distribution of TSS distance to gene start; PWM—position weight matrix; pHMMs—profile hidden Markov models; DSP₂—DNA curvature, SIDD, stacking energy; DDS—DNA duplex stability; Fuzzy-AIRS—Artificial Immune Recognition System with Fuzzy resource allocation mechanism; vw Z-curve—variable-window Z-curve; PLS—partial least squares; PseKNC—pseudo–K-tuple nucleotide composition; PE—promoter elements including −10, −35, −15 and AT-rich UP elements, together with the new TSS motifs by the authors; DPE—distances (d) between promoter elements (contains d(−10/−35), d(−10/TSS) and d(−15/−10)); TFBSD—TFBSs density; PCP—physico-chemical properties (i.e. free energy, base stacking, entropy and melting temperature); RF—random forest; PSTNP_SS/PSTNP_DS—position-specific trinucleotide propensity based on single-stranded or double-stranded characteristic, PseEIIP—electron–ion interaction pseudo-potentials of trinucleotide; PseZNC—pseudo–multi-window Z-curve nucleotide composition; NSM—nucleotide statistical measure; ASPC—approximate signal pattern count; PSO—position specific occurrences; DN—distribution of nucleotides; LR—logistic regression; BPB—bi-profile Bayesian signatures; KNC—k-tuple nucleotide composition; DAC—dinucleotide-based auto-covariance; EL—ensemble learning; CKSNAP—composition of k-spaced nucleic acid pairs; PCPseDNC—parallel correlation pseudo-dinucleotide composition; GBDT—gradient boosting decision tree; DE—relative stability (the difference in free energy); PCSF—position-correlation scoring function.

^bThe URL addresses for the listed tools: iPro54-PseKNC—http://lin-group.cn/server/iPro54-PseKNC; iPromoter-2L—http://bioinformatics.hitsz.edu.cn/iPromoter-2L/; 70ProPred—http://server.malab.cn/70ProPred/; iPro70-PseZNC—http://lin-group.cn/server/iPro70-PseZNC; iPro70-FMWin—http://ipro70.pythonanywhere.com/server; iPromoter-FSEn—http://ipromoterfsen.pythonanywhere.com/server; iPSW(2L)-PseKNC—http://www.jci-bioinfo.cn/iPSW(2L)-PseKNC; MULTiPly—http://flagshipnt.erc.monash.edu/MULTiPly/; iPromoter-2L2.0—http://bliulab.net/iPromoter-2L2.0/; SELECTOR—http://SELECTOR.erc.monash.edu/; PromPredict— http://nucleix.mbu.iisc.ernet.in/prompredict/prompredict.html; BacPP—http://bacpp.bioinfoucs.com/home.

^cYes—The approach is accompanied with a webserver/tool and it is still working; Decommissioned—The webserver/tool is no longer available; No—The approach has no webserver or tool; Yes^*—The server/tool was not involved in our performance comparison due to the unavailable pretrained model, unavailable latest test data or the unmatched sequence length.

^dWe listed the detailed prokaryotic promoter types based on the description in the papers. ‘–’ demonstrates such information is not present in the paper.

^eThe species information of the sequences used in corresponding studies was directly extracted from the studies. For some species, the Latin names have been provided according to the predictors; for other species, based on the information provided in the papers, we just provided the general names of the species when their Latin names are not available.

^f‘–’ demonstrates that no clearly length information is provided in the paper.