 Research
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Generating normal networks via leaf insertion and nearest neighbor interchange
BMC Bioinformatics volume 20, Article number: 642 (2019)
Abstract
Background
Galled trees are studied as a recombination model in theoretical population genetics. This class of phylogenetic networks has been generalized to treechild networks and other network classes by relaxing a structural condition imposed on galled trees. Although these networks are simple, their topological structures have yet to be fully understood.
Results
It is wellknown that all phylogenetic trees on n taxa can be generated by the insertion of the nth taxa to each edge of all the phylogenetic trees on n−1 taxa. We prove that all treechild (resp. normal) networks with k reticulate nodes on n taxa can be uniquely generated via three operations from all the treechild (resp. normal) networks with k−1 or k reticulate nodes on n−1 taxa. Applying this result to counting rooted phylogenetic networks, we show that there are exactly \(\frac {(2n)!}{2^{n} (n1)!}2^{n1} n!\) binary phylogenetic networks with one reticulate node on n taxa.
Conclusions
The work makes two contributions to understand normal networks. One is a generalization of an enumeration procedure for phylogenetic trees into one for normal networks. Another is simple formulas for counting normal networks and phylogenetic networks that have only one reticulate node.
Background
Phylogenetic networks have been used to date both vertical and horizontal genetic transfers in evolutionary genomics and population genetics in the past two decades [1–3]. A rooted phylogenetic network (RPN) is a directed acyclic digraph in which all the sink nodes are of indegree 1 and a unique source node is designated as the root, where the former represent a set of taxa (e.g, species, genes, or individuals in a population) and the latter represents the least common ancestor of the taxa. Moreover, the other nodes in a RPN are divided into tree nodes and reticulate nodes, where reticulate nodes represent reticulate evolutionary events such as horizontal genetic transfers and genetic recombination.
The topological properties of RPNs are much more complicated than phylogenetic trees [2, 4, 5]. Therefore, different mathematical issues arise in the study of RPNs. First, phylogenetic reconstruction problems are often NPhard even for trees [6, 7]. As such, a phylogenetic reconstruction method often uses nearest neighbor interchanges (NNIs) or other rearrangement operations to search for an optimal tree or network [8, 9]. Recently, different variants of NNI have been proposed for RPNs [10–16].
Second, to develop efficient algorithms for NPcomplete problems on RPNs, simple classes of RPNs have been introduced, including galled trees [17, 18], treechild networks (TCNs) [19], normal networks [20], reticulationvisible networks [4] and treebased networks [21, 22] (see also [5, 23]). For instance, a RPN is a TCN if every nonleaf node has a child that is a tree node or a leaf. Although these network classes have been intensively investigated, their topological structures remain unclear [5, 24]. How to efficiently enumerate and count normal networks remains unclear [25–30].
This work makes two contributions to understanding TCNs and normal networks. It is a wellknown fact that all phylogenetic trees on n taxa can be generated by inserting the nth taxa in every edge of all the phylogenetic trees on n−1 taxa. We prove that all TCNs with k reticulate nodes on n taxa can be uniquely generated via three operations from TCNs with k−1 or k reticu late nodes on n−1 taxa (Theorem 1, “Generating TCNs and normal networks” section). Using this fact, we obtain recurrence formulas for counting TCNs and normal networks (“Counting formulas” section). In particular, simple formulas are given for the number of RPNs and normal networks with one reticulate node, respectively.
Methods
Basic notation
A RPN over a finite set of taxa X is an acyclic digraph such that:
there is a unique node of indegree 0 and outdegree 1, called the root;
there are exactly X nodes of outdegree 0 and indegree 1, called the leaves of the RPN, each being labeled with a unique taxon in X;
each nonleaf/nonroot node is either a reticulate node that is of indegree 2 and outdegree 1, or a tree node that is of indegree 1 and outdegree 2; and
there are no parallel edges between a pair of nodes.
Two RPNs are drawn in Fig. 1, where each edge is directed away from the root and both the root and edge orientation are omitted. For a RPN N, we use \({\mathcal {V}}(N), {\mathcal {R}}(N), {\mathcal {T}}(N)\) and \({\mathcal {E}}(N)\) to denote the set of all nodes, the set of reticulate nodes and the set of tree nodes and the set of directed edges for N, respectively.
Let \(u\in {\mathcal {V}}(N)\) and \(v\in {\mathcal {V}}(N)\). The node u is said to be a parent (resp. a child) of v if \((u, v)\in {\mathcal {E}}(N)\) (resp. \((v, u)\in {\mathcal {E}}(N)\)). Every reticulate node r has a unique child, named c(r), whereas every tree node t has a unique parent, named p(t). Furthermore, u is an ancestor of v or, equivalently, v is belowu if there is a direct path from the network root to v that contains u. We say that u and v are incomparable if neither of them is an ancestor of the other.
Let \(e=(u, v)\in {\mathcal {E}}(N)\). It is a reticulate edge if v is a reticulate node and a tree edge otherwise. Hence, a tree edge leads to either a tree node or a leaf.
A phylogenetic tree is simply a RPN with no reticulate nodes.
A TCN is a RPN in which every nonleaf node has a child that is a tree node or a leaf or, equivalently, there is a path from every nonleaf node to some leaf that consists only of tree edges. Both RPNs in Fig. 1 are treechild.
A normal network is a TCN in which every reticulate node satisfies the following condition:
(The normal condition) The two parents are incomparable.
The first PRN in Fig. 1 is not normal, as a parent of the left most reticulate node is an ancestor of the other in the network.
Generating TCNs and normal networks
We define the following rearrangement operations for TCNs N on [1,n], which are illustrated in Fig. 2:
Leaf insertion For a tree edge \(e=(u, v)\in {\mathcal {E}}(N)\), insert a new node w to subdivide e and attach Leaf n+1 below w as its child. The resulting network is denoted by LeafInsert(N,e,n+1), in which w is a tree node.
Reticulation insertion For a pair of tree edges e_{1}=(u_{1},v_{1}) and e_{2}=(u_{2},v_{2}) of N, which are not necessarily distinct, insert a new node w_{1} to subdivide e_{1} and a new node w_{2} to subdivide e_{2}, attach a new reticulate node r as the common child of w_{1} and w_{2} and make Leaf (n+1) to be the child of r. In this case, we say that rstraddles e_{1} and e_{2}. We use RetInsert(N,e_{1},e_{2},n+1) to denote the resulting network. We simply write RetInsert(N,e,n+1) if e_{1}=e_{2}=e.
Child rotation Let r be a reticulate node with parents \(u \in {\mathcal {T}}(N)\) and v. If u is not an ancestor of v, exchange the unique child of r and the other child of u. The resulting network is denoted by CRotate(N,u,r).
Note that a child rotation is a special case of the rNNI rearrangement introduced by Gambette et al. in [12]. Let \({\mathcal {T}CN}_{k}(n)\) denote the set of TCNs with k reticulations on [1,n].
Proposition 1
Let \(M\in {\mathcal {T}CN}_{k}(n)\) and let e_{1} and e_{2} be two tree edges of M. Then,
Proof
The second statement is a special case of the first. Let e_{1}=(u,v) and e_{2}=(x,y). Since e_{1} and e_{2} are tree edges, both v and y are tree nodes or leaves. Let r be the added reticulate node. Then the parents of r have v and y as their child, respectively, the nodes u and x have the parents of r as their tree node child; Leaf n+1 is the tree child r. Additionally, all the other nodes have the same children as in M. Therefore, RetInsert(M,e_{1},e_{2},n+1) is a TCN. □
Proposition 2
Let \(M\in {\mathcal {T}CN}_{k+1}(n+1)\). Assume that \(r\in {\mathcal {R}}(M)\) and its parents are u and v such that u is not an ancestor of v in M. Then,
Proof
Let M^{′}=CRotate(M,u,r). Since u is a parent of r and M is treechild, u is a tree node. Let w be the other child of u and let z be the unique child of r. Since M is treechild, z and w are tree nodes (see Fig. 2). The tree node z becomes the child of u Therefore, every node also has a child that is a tree node or a leaf in M^{′}. □
By definition, w becomes a child of r and z becomes a tree node child of u in M^{′}. If M^{′} contains a directed cycle C, C must contain v and w, implying that u is an ancestor of v in M, a contradiction. Therefore, M^{′} is acyclic and \(M' \in {\mathcal {T}CN}_{k+1}(n+1)\).
Proposition 3
Let \(N\in {\mathcal {T}CN}_{k+1}(n+1)\).
(i) If Leaf (n+1) is the child of a reticulate node r, N can then be obtained from an \(M\in {\mathcal {T}CN}_{k}(n)\) via a reticulation insertion.
(ii) If Leaf (n+1) is the child of a tree node t and the sibling of n+1 is also a tree node, N can then obtained from an \(M\in {\mathcal {T}CN}_{k+1}(n)\) via a leaf insertion.
(iii) If Leaf (n+1) is a child of a tree node t and the sibling of n+1 is a reticulate node, N can then be obtained from an \(M\in {\mathcal {T}CN}_{k+1}(n+1)\) via a child rotation.
Proof
(i) Let r have parents u_{1} and u_{2} in N. Since N is a TCN, u_{1} and u_{2} are tree nodes and so are their children other than r. Let w_{i} and v_{i} be the parent and the child of u_{i} such that v_{i}≠r, respectively, for each i=1,2. Since r is a reticulate node, v_{1} and v_{2} are tree nodes. Without loss of generality, we assume that u_{2} is not the parent of u_{1}. There are two cases for consideration.
If u_{1} is the parent of u_{2}, then u_{1}=w_{2} and u_{2}=v_{1} (Fig. 3a). Removing Leaf (n+1),u_{1} and u_{2} (together with incident edges) and adding an edge e=(w_{1},v_{2}) produce a TCN M with k reticulations such that N=RetInsert(M,e,n+1).
If u_{1} is not the parent of u_{2}, then, w_{1}≠u_{2} (Fig. 3b). After removing Leaf n+1,u_{1} and u_{2} (together with incident edges) and adding two edges e_{i}=(w_{i},v_{i}) (i=1,2), we obtain a TCN M such that N=RetInsert(M,e_{1},e_{2},n+1).
(ii) Let u be the parent of t and let v be the sibling of Leaf n+1 (Fig. 3c). By assumption, v is a tree node. After removing t and Leaf (n+1) (together with incident edges) and adding e=(u,v), we obtain a TCN \(M\in {\mathcal {T}CN}_{k+1}(n)\) such that N=LeafInsert(M,(u,v),n+1).
(iii) Let y be the sibling of n+1 that is a reticulate node (Fig. 3d). Let z be the child of y and let M=CRotate(N,t,y). Since z is below y and y is below t in N, neither attaching the tree node z below t nor attaching Leaf (n+1) below y generates a directed cycle in M. Hence, \(M\in {\mathcal {T}CN}_{k+1}(n+1)\) in which Leaf (n+1) is the child of a reticulate node y such that N=CRotate(M,t,y). □
Proposition 4
Let \(N_{1}, N_{2} \in {\mathcal {T}CN}_{k}(n)\).
(i) LeafInsert(N_{1},e_{1},n+1) is identical to LeafInsert(N_{2},e_{2},n+1) iff N_{1}=N_{2} and e_{1}=e_{2}.
(ii) RetInsert(N_{1},e_{1},e1′,n+1) is identical to RetInsert(N_{2},e_{2},e2′,n+1) iff N_{1}=N_{2}.
(iii) Assume the parent of Leaf n is a reticulate node y_{i} in N_{i} for i=1,2. CRotate(N_{1},x_{1},y_{1}) is identical to CRotate(N_{2},x_{2},y_{2}) iff N_{1}=N_{2}.
Proof
(i) Let \(N_{i} \in {\mathcal {T}CN}_{k}(n)\) and \(e_{i}\in {\mathcal {V}}(N_{i}), i=1, 2\). Let M_{1}=LeafInsert(N_{1},e_{1},n+1) and M_{2}=LeafInsert(N_{2},e_{2},n+1) such that M_{1}=M_{2}. Then, there exists a node mapping ϕ from M_{1} to M_{2} such that (i) it maps a leaf in M_{1} to the same leaf and (ii) \((\phi (u), \phi (v))\in {\mathcal {E}}(M_{2})\) if and only if \((u, v)\in {\mathcal {E}}(M_{1})\). Since n+1 is inserted as a leaf, ϕ maps the parent p_{1} of (n+1) in M_{1} to the parent p_{2} of n+1 in M_{2}, implying that ϕ induces an isomorphic mapping from N_{1} to N_{2}. This proves the necessity condition. The sufficient condition is straightforward.
(ii) and (iii) Both statement can be proved similarly. The proposition is proved. □
Results
Main theorems
Taken together, Propositions 1–4 imply the following theorem.
Theorem 1
Each TCN of \({\mathcal {T}CN}_{k+1}(n+1)\) can be obtained from either (i) a unique TCN of \({\mathcal {T}CN}_{k+1}(n)\) by attaching Leaf n+1 to a tree edge or (ii) a unique TCN \(N\in {\mathcal {T}CN}_{k}(n)\) by applying one of the following operations:
Insertion of a reticulate node r with the child Leaf (n+1) into a tree edge or straddling two tree edges;
Insert r into a tree edge (u,v), as described in (a), and then conduct the child rotation to switch the child of r and the tree node child of v.
Insert r straddling two tree edges e^{′}=(u^{′},v^{′}) and e^{′′}=(u^{′′},v^{′′}), as described in (a), and then conduct the child rotation to switch the child of r and the tree node child of v^{′′} (resp. v^{′}) if u^{′′} (resp. u^{′}) is not an ancestor of u^{′} (resp. u^{′′}).
If we restrict the operations on normal networks, we obtain all the normal networks in \({\mathcal {T}CN}_{k+1}(n+1)\). However, inserting a reticulate node and then applying the child rotation may lead to a scenario that a reticulation no longer satisfy the normal condition (Fig. 5). Hence, the childrotation operation should be taken after some verification when all normal networks are enumerated.
Theorem 2
Each normal network of \({\mathcal {T}CN}_{k+1}(n+1)\) can be obtained from either (i) a unique normal network in \({\mathcal {T}CN}_{k+1}(n)\) by attaching Leaf n+1 to a tree edge or (ii) a unique normal network \(N\in {\mathcal {T}CN}_{k}(n)\) by applying one of the following operations for each pair of incomparable edges e_{1}=(u_{1},v_{1}) and e_{2}=(u_{2},v_{2}) in N:
Insert a reticulate node r with the child (n+1) straddling e_{1} and e_{2}. Let p_{i} be the tree node inserted into e_{i} for i=1,2.
Insert r as described in (a) and then conduct the child rotation to make v_{1} to be the child of r and n+1 the child of p_{1}, respectively, unless a reticulate edge (x,y) exists in N (Fig. 5) such that:
y is below v_{1};
x is not an ancestor of v_{1};
x is an ancestor of v_{2}.
Insert r as described in (a) and then conduct the child rotation to make v_{2} to be the child of r and n+1 the child of p_{2}, respectively, unless a reticulate edge (x,y) exists in N such that:
y is below v_{2};
x is not an ancestor of v_{2};
x is an ancestor of v_{1}.
Proof
The statement for normal networks is based on the fact that if N is obtained from N^{′} vis one of the three operations given in Theorem 1, that the normality of N implies the normality of N^{′}.
The conditions in (b) and (c) are used to exclude the child rotations that make the normal condition invalid for some existing reticulate nodes in the generated TCN. □
Counting formulas
Let N be a TCN. For a pair of edges (u_{1},v_{1}) and (u_{2},v_{2}) of N, they are incomparable if neither of v_{1} and v_{2} is an ancestor of the other. Let u(N) be the number of unordered pairs of incomparable edges in N and let:
Define a_{n,k} to be \({\mathcal {T}CN}_{k}(n), 0\leq k< n\) and b_{n,k} to be the number of normal networks in TCN_{k}(n),0≤k<n.
Theorem 3
(i) The a_{n,k} can be calculated through the following recurrence formula:
where a_{2,0}=1 and u_{n−1,k−1} is defined in Eq. (1).
(ii) The b_{n,1} can be calculated through the following recurrence formula:
where u_{n−1,0} is the total number of unordered pairs of incomparable edges in all the phylogenetic trees on n−1 taxa.
Proof
(i) The unique tree on two taxa is a TCN and thus a_{2,0}=1.
Each TCN of \({\mathcal {T}CN}_{k}(n1)\) has 2n+k−3 tree edges and Leaf n can be attached to each of these edges. The first term of the right hand side of Eq. (2) counts the TCNs obtained by applying the leaf insertion in Theorem 1.
Consider \(N\in {\mathcal {T}CN}_{k1}(n1)\). N has n−1 leaves, n+k−3 tree nodes, and thus 2n+k−4 tree edges. The reticulation insertion can be used on a single edge or a pair of edges in N. Thus, we can insert a reticulate node r with the child Leaf n in \(2n+k4 +{2n+k4 \choose 2}=(2n+k3)(2n+k4)/2\) possible ways. After the insertion of r in a tree edge (u,v), we can apply a child rotation to exchange Leaf n with v, as u is not an ancestor of v after r was inserted. Similarly, after r is connected to a pair of edges e_{1} and e_{2}, we can apply a child rotation once if one edge is below the other and in two possible ways if neither is an ancestor of the other.
In summary, for each unordered pair of tree edges (e_{1},e_{2}), we can generate three different tree child networks with k reticulations on [1,n] if they are incomparable and two otherwise. Thus, we have the second and third terms of the formula.
(ii) The fact that b_{n,n−1}=0 was first proved by Bickner [25]. □
In the case that n>2 and k≤n−2, Eq. (3) for b_{n,1} follows from the following two facts:
Only two incomparable edges in normal networks in \({\mathcal {T}CN}_{k1}(n1)\) can be used to generate normal networks in \({\mathcal {T}CN}_{k}(n)\);
For each unordered pair of incomparable edges in a tree on [1,n−1], three normal networks can be obtained by applying insertion of reticulate node and two child rotations.
Unfortunately, we do not know how to obtain a simple formula for b_{n,k} in general. By Theorem 3, one still can compute the number of normal networks with k reticulate nodes on [1,n],b_{n,k}, by enumeration. For each 1≤k≤n−2 and 3≤n≤7,b_{n,k} is listed in Table 1.
It is challenging to obtain a simple formula for counting u_{n,k} for arbitrary k. But we can find a closed formula for u_{n,0} and thus obtain a recurrence formula for a_{n,1} and b_{n,1}.
Lemma 1
For any n≥2, the total number of unordered pairs of incomparable edges in all the phylogenetic trees on n taxa is:
Proof
Let T be a phylogenetic tree on [1,n−1] and let O(T) denote the set of ordered pairs of comparable edges in T, where that (x,y)∈O(T) means the edge x is above the edge y. Then, it is not hard to verify:
□
Assume T^{′} is obtained from T by attaching Leaf n in an edge e=(u,v). In T^{′}, the parent w of Leaf n is the tree node inserted in e, implying that e is subdivided into two edges of T^{′}:
and
Thus,
Hence,
Since T has 2n−3 edges,
where \(\mathcal {LI}(T, n)\) denotes the set of 2n−3 phylogenetic trees that are obtained by a LeafInsertion on T.
Let c_{n} be the total number of unordered pairs of comparable edges in all the phylogenetic trees on n taxa. Clearly, c_{2}=2. Since there are \(\frac {(2n4)!}{2^{n2}(n2)!}\) phylogenetic trees with n−1 leaves, which each have 2n−3 edges, Eq. (5) implies:
or, equivalently,
Therefore,
where \(\frac {(2k)!}{(k+1)!k!}\) is the kth Catalan number C_{k} that is equal to the integral appearing above ([31]). Since there are \(\frac {(2n2)!}{2^{n1}(n1)!}\) phylogenetic trees on [1,n] each having (2n−1) edges,
Theorem 4
For any n≥3, the numbers of TCNs and normal networks with exactly one reticulate node on n taxa are:
and
respectively.
Proof
Since \(a_{n1, 0}=\frac {(2n4)!}{2^{n2}(n2)!}\), by Theorem 3,
or, equivalently,
Therefore, since a_{2,1}=2,
By induction, we can show that \(\sum ^{n}_{k=0}{2k\choose k}4^{k}=\frac {(2n+1)!}{2^{2n}(n!)^{2}}\) and \(\sum ^{n}_{k=0}{2k\choose k}k4^{k}=\frac {(2n+1)!}{3\cdot 2^{2n}n!(n1)!}\). Continuing the above calculation, we obtain:
□
This proves Eq. (6).
Similarly, by Theorem 3 and Lemma 1, we have:
or, equivalently,
Since b_{2,1}=0,
This proves Eq. (7).
Remark 1
Every RPN with exactly one reticulate node is a TCN. Therefore, a_{n,1} is actually the number of RPNs with one reticulate node.
Conclusions
It is wellknown that all phylogenetic trees on n taxa can be generated by the insertion of the nth taxa in each edge of all the phylogenetic trees on the first n−1 taxa. The main result of this work is a generalization of this fact into TCNs. This leads to a simple procedure for enumerating both normal networks and TCNs, the Ccode for which is available upon request. It is fast enough to count all the normal networks on eight taxa. Recently, Cardona et al. introduced a novel operation to enumerate TCNs. Their program was successfully used to compute the exact number of treechild networks on six taxa. Although our program is faster than theirs, it still cannot be used to count TCNs on eight taxa on a PC.
Another contribution of this work is Eq. (6) and (7) for counting RPNs with exactly one reticulate node. Semple and Steel [30] presented formulas for counting unrooted networks with one reticulate node. Since an unrooted networks can be oriented into a different number of RPNs, it is note clear how to use their results to derive a formula for the count of RPNs. Bouvel et al. [26] presented a formula for counting RPNs with one reticulate node. Our formula is much simpler than the formula given in [26].
Lastly, the following problem is open:
Is there a simple formula like Eq. (6) for the count of TCNs with k reticulate nodes on n taxa for each k>1?
Availability of data and materials
Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.
Abbreviations
 NNI:

Nearest neighbor interchange
 RPN:

Rooted phylogenetic network
 TCN:

Treechild network
References
 1
Doolittle WF. Phylogenetic classification and the universal tree. Science. 1999; 284(5423):2124–8.
 2
Gusfield D. ReCombinatorics: the Algorithmics of Ancestral Recombination Graphs and Explicit Phylogenetic Networks. Cambridge, USA: MIT Press; 2014.
 3
Jain R, Rivera MC, Lake JA. Horizontal gene transfer among genomes: the complexity hypothesis. Proc Natl Acad Sci. 1999; 96(7):3801–6.
 4
Huson DH, Rupp R, Scornavacca C. Phylogenetic Networks: Concepts, Algorithms and Applications. Cambridge, UK: Cambridge University Press; 2010.
 5
Steel M. Phylogeny: Discrete and Random Processes in Evolution. Philadelphia, USA: SIAM; 2016.
 6
Chor B, Tuller T. Finding a maximum likelihood tree is hard. J ACM (JACM). 2006; 53(5):722–44.
 7
Foulds LR, Graham RL. The steiner problem in phylogeny is npcomplete. Adv Appl Math. 1982; 3(1):43–9.
 8
Felsenstein J. Inferring Phylogenies, vol. 2. Sunderland: Sinauer Associates; 2004.
 9
Yu Y, Dong J, Liu KJ, Nakhleh L. Maximum likelihood inference of reticulate evolutionary histories. Proc Natl Acad Sci. 2014; 111(46):16448–53.
 10
Bordewich M, Linz S, Semple C. Lost in space? Generalising subtree prune and regraft to spaces of phylogenetic networks. J Theor Biol. 2017; 423:1–12.
 11
Francis A, Huber KT, Moulton V, Wu T. Bounds for phylogenetic network space metrics. J Math Biol. 2018; 76(5):1229–48.
 12
Gambette P, Van Iersel L, Jones M, Lafond M, Pardi F, Scornavacca C. Rearrangement moves on rooted phylogenetic networks. PLoS Comput Biol. 2017; 13(8):1005611.
 13
Huber KT, Linz S, Moulton V, Wu T. Spaces of phylogenetic networks from generalized nearestneighbor interchange operations. J Math Biol. 2016; 72(3):699–725.
 14
Huber KT, Moulton V, Wu T. Transforming phylogenetic networks: Moving beyond tree space. J Theor Biol. 2016; 404:30–9.
 15
Janssen R, Jones M, Erdős PL, Van Iersel L, Scornavacca C. Exploring the tiers of rooted phylogenetic network space using tail moves. Bull Math Biol. 2018; 80(8):2177–208.
 16
Klawitter J, Linz S. On the subnet prune and regraft distance. Electron J Combin. 2019; 26:2–3.
 17
Gusfield D, Eddhu S, Langley C. The fine structure of galls in phylogenetic networks. INFORMS J Comput. 2004; 16(4):459–69.
 18
Wang L, Zhang K, Zhang L. Perfect phylogenetic networks with recombination. J Comput Biol. 2001; 8(1):69–78.
 19
Cardona G, Rossello F, Valiente G. IEEE/ACM Trans Comput Biol Bioinforma (TCBB). 2009; 6(4):552–569.
 20
Willson SJ. Unique determination of some homoplasies at hybridization events. Bull Math Biol. 2007; 69(5):1709–25.
 21
Francis AR, Steel M. Which phylogenetic networks are merely trees with additional arcs?Syst Biol. 2015; 64(5):768–77.
 22
Zhang L. On treebased phylogenetic networks. J Comput Biol. 2016; 23(7):553–65.
 23
Zhang L. Clusters, trees, and phylogenetic network classes. In: Bioinformatics and Phylogenetics. New York: Springer: 2019. p. 277–315.
 24
Gunawan AD, Yan H, Zhang L. Compression of phylogenetic networks and algorithm for the tree containment problem. J Comput Biol. 2019; 26(3):285–94.
 25
Bickner DR. On normal networks. PhD thesis, Iowa State University, Department of Mathematics. 2012.
 26
Bouvel M, Gambette P, Mansouri M. Counting levelk phylogenetic networks. arXiv preprint arXiv:1909.10460. 2019.
 27
Cardona G, Pons JC, Scornavacca C. Generation of Binary TreeChild phylogenetic networks. PLoS Computat Biol. 2019; 15(9):e1007347.
 28
Fuchs M, Gittenberger B, Mansouri M. Counting phylogenetic networks with few reticulation vertices: treechild and normal networks. Australas J Comb. 2019; 73(2):385–423.
 29
McDiarmid C, Semple C, Welsh D. Counting phylogenetic networks. Ann Comb. 2015; 19(1):205–24.
 30
Semple C, Steel M. IEEE/ACM Trans Comput Biol Bioinforma (TCBB). 2006; 3(1):84.
 31
Stanley RP. Catalan Numbers. Cambridge, UK: Cambridge University Press; 2015.
Acknowledgements
The author thanks Mike Steel for useful discussion of counting networks and comments on the manuscript and Yurui Chen for implementing the implementation of the enumeration method given in this work. He also thanks anonymous reviewers and Jonathan Klawitter for useful feedback on the first draft of this paper.
About this supplement
This article has been published as part of BMC Bioinformatics Volume 20 Supplement 20, 2019: Proceedings of the 17th Annual Research in Computational Molecular Biology (RECOMB) Comparative Genomics Satellite Workshop: Bioinformatics. The full contents of the supplement are available online at https://bmcbioinformatics.biomedcentral.com/articles/supplements/volume20supplement20.
Funding
Publication costs of this work are funded by Singapore’s Ministry of Education Academic Research Fund Tier1 [grant R146000238114] and the National Research Fund [grant NRF2016NRFNSFC001026].
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Zhang, L. Generating normal networks via leaf insertion and nearest neighbor interchange. BMC Bioinformatics 20, 642 (2019). https://doi.org/10.1186/s1285901932093
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DOI: https://doi.org/10.1186/s1285901932093
Keywords
 Treechild networks
 normal networks